@article{Song24_SR,
  title = {A new approach to three-dimensional microstructure reconstruction of a polycrystalline solar cell using high-efficiency {C}u({I}n,{G}a){S}e2},
  author = {Song, Chang-Yun and Maiberg, Matthias and Kempa, Heiko and Witte, Wolfram and Hariskos, Dimitrios and Abou-Ras, Daniel and Moeller, Birgit and Scheer, Roland and Gholinia, Ali},
  year = {2024},
  journal = {Scientific Reports},
  volume = {14},
  number = {1},
  pages = {2036},
  publisher = {Nature Publishing Group UK London},
  doi = {10.1038/s41598-024-52436-2},
  url = {https://www.nature.com/articles/s41598-024-52436-2},
  abstract = {A new method for efficiently converting electron backscatter diffraction data obtained using serial sectioning by focused ion beam of a polycrystalline thin film into a computational, three-dimensional (3D) structure is presented. The reported data processing method results in a more accurate representation of the grain surfaces, reduced computer memory usage, and improved processing speed compared to traditional voxel methods. The grain structure of a polycrystalline absorption layer from a high-efficiency Cu(In,Ga)Se2 solar cell (19.5\%) is reconstructed in 3D and the grain size and surface distribution is investigated. The grain size distribution is found to be best fitted by a log-normal distribution. We further find that the grain size is determined by the [Ga]/([Ga] + [In]) ratio in vertical direction, which was measured by glow discharge optical emission spectroscopy. Finally, the 3D model derived from the structural information is applied in optoelectronic simulations, revealing insights into the effects of grain boundary recombination on the open-circuit voltage of the solar cell. An accurate 3D structure like the one obtained with our method is a prerequisite for a detailed understanding of mechanical properties and for advanced optical and electronic simulations of polycrystalline thin films.}
}
@incollection{Klemm23_TPC,
  author = {Klemm, Sandra and Buhl, Jonas and M{\"o}ller, Birgit and B{\"u}rstenbinder, Katharina},
  editor = {Hussey, Patrick J. and Wang, Pengwei},
  title = {Quantitative Analysis of Microtubule Organization in Leaf Epidermis Pavement Cells},
  booktitle = {The Plant Cytoskeleton: Methods and Protocols},
  year = {2023},
  publisher = {Springer US},
  address = {New York, NY},
  pages = {43--61},
  abstract = {Leaf epidermis pavement cells form highly complex shapes with interlocking lobes and necks at their anticlinal walls. The microtubule cytoskeleton plays essential roles in pavement cell morphogenesis, in particular at necks. Vice versa, shape generates stress patterns that regulate microtubule organization. Genetic or pharmacological perturbations that affect pavement cell shape often affect microtubule organization. Pavement cell shape and microtubule organization are therefore closely interconnected. Here, we present commonly used approaches for the quantitative analysis of pavement cell shape characteristics and of microtubule organization. In combination with ablation experiments, these methods can be applied to investigate how different genotypes (or treatments) affect the organization and stress responsiveness of the microtubule cytoskeleton.},
  isbn = {978-1-0716-2867-6},
  doi = {10.1007/978-1-0716-2867-6_4},
  url = {https://doi.org/10.1007/978-1-0716-2867-6_4}
}
@book{Moeller22_Habil,
  title = {Image analysis in the life sciences: computational methods and tools},
  author = {M{\"o}ller, Birgit},
  year = {2022},
  publisher = {Martin Luther University Halle-Wittenberg},
  series = {Habilitation {T}hesis},
  url = {https://search.ebscohost.com/login.aspx?direct=true&db=cat09315a&AN=ulb.1842691589&lang=de&site=eds-live&scope=site},
  keywords = {image analysis, spot detection, segmentation, active contours, machine learning, Alida, MiToBo, life sciences, cells, roots},
  abstract = {This habilitation thesis presents methodical and computational approaches for the analysis of image data in various application domains of the life sciences. Amongst others methods for the detection of punctiform structures in microscope images are described. A second research field deals with the segmentation of more complex objects like cells or plant roots. Here established methods like active contours have specifically been extended as well as new methods of machine learning with neural networks been applied. A third topic area comprises the extraction of quantitative data of objects. Here new measures for cell shape have been devised as well as protocols for the quantification and comparison of subcellular structures been developed. In addition to the methodical approaches the software libraries Alida and MiToBo are presented, which yield the basis for the implementation of most of the approaches, and the annotation tool rhizoTrak.}
}
@inproceedings{Moeller21_CVPPA,
  title = {{Analysis of Arabidopsis Root Images - Studies on CNNs and Skeleton-Based Root Topology}},
  author = {B.~M{\"o}ller and B.~Schreck and S.~Posch},
  booktitle = {{Proc. of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 7th Workshop on Computer Vision in Plant Phenotyping and Agriculture (CVPPA)}},
  year = {2021},
  pages = {1294-1302},
  month = {October},
  doi = {10.1109/ICCVW54120.2021.00150},
  url = {https://openaccess.thecvf.com/content/ICCV2021W/CVPPA/html/Moller_Analysis_of_Arabidopsis_Root_Images_--_Studies_on_CNNs_and_ICCVW_2021_paper.html},
  abstract = {Roots and their temporal development play an important role in plant research. Over the decades image-based monitoring of root growth has become a key methodology in this research field. The growing amount of image data is often tackled with automatic image analysis approaches. In particular convolutional neural networks (CNNs) recently gained increasing interest for root segmentation. This segmentation of roots is usually only the first step of an analysis pipeline and needs to be supplemented by topological reconstruction of the complete root system architecture. 
In this paper we present a comprehensive study of different CNN architectures, loss functions and parameter settings for root image segmentation. In addition, we show how main and lateral roots can be identified based on the skeletons of segmented root components as a first step towards topological reconstruction of root system architecture. We present quantitative and qualitative results on data released in the course of the CVPPA Arabidopsis Root Segmentation Challenge 2021.}
}
@incollection{Poeschl20_MBC,
  title = {User-friendly assessment of pavement cell shape features with PaCeQuant: Novel functions and tools},
  series = {Methods in Cell Biology},
  publisher = {Academic Press},
  volume = {160},
  pages = {349-363},
  year = {2020},
  booktitle = {Plant Cell Biology},
  issn = {0091-679X},
  doi = {https://doi.org/10.1016/bs.mcb.2020.04.010},
  url = {http://www.sciencedirect.com/science/article/pii/S0091679X20300741},
  author = {Yvonne Poeschl and Birgit Möller and Lukas Müller and Katharina Bürstenbinder},
  keywords = {Cell segmentation, Feature extraction, Pavement cells, ImageJ, MiToBo, PaCeQuant, Arabidopsis},
  abstract = {Leaf epidermis pavement cells develop complex jigsaw puzzle-like shapes in many plant species, including the model plant Arabidopsis thaliana. Due to their complex morphology, pavement cells have become a popular model system to study shape formation and coordination of growth in the context of mechanically coupled cells at the tissue level. To facilitate robust assessment and analysis of pavement cell shape characteristics in a high-throughput fashion, we have developed PaCeQuant and a collection of supplemental tools. The ImageJ-based MiToBo plugin PaCeQuant supports fully automatic segmentation of cell contours from microscopy images and the extraction of 28 shape features for each detected cell. These features now also include the Largest Empty Circle criterion as a proxy for mechanical stress. In addition, PaCeQuant provides a set of eight features for individual lobes, including the categorization as type I and type II lobes at two- and three-cell junctions, respectively. The segmentation and feature extraction results of PaCeQuant depend on the quality of input images. To allow for corrections in case of local segmentation errors, the LabelImageEditor is provided for user-friendly manual postprocessing of segmentation results. For statistical analysis and visualization, PaCeQuant is supplemented with the R package PaCeQuantAna, which provides statistical analysis functions and supports the generation of publication-ready plots in ready-to-use R workflows. In addition, we recently released the FeatureColorMapper tool which overlays feature values over cell regions for user-friendly visual exploration of selected features in a set of analyzed cells.}
}
@article{Moeller19_PS,
  author = {Birgit M{\"o}ller and Hongmei Chen and Tino Schmidt and Axel Zieschank and Roman Patzak and Manfred T{\"u}rke and Alexandra Weigelt and Stefan Posch},
  title = {rhizo{T}rak: A flexible open source {F}iji plugin for user-friendly manual annotation of time-series images from minirhizotrons},
  journal = {Plant and Soil},
  year = {2019},
  number = {444},
  pages = {519-534},
  month = {Sep},
  day = {10},
  abstract = {Background and aims: Minirhizotrons are commonly used to study root turnover which is essential for understanding ecosystem carbon and nutrient cycling. Yet, extracting data from minirhizotron images requires extensive annotation effort. Existing annotation tools often lack flexibility and provide only a subset of the required functionality. To facilitate efficient root annotation in minirhizotrons, we present the user-friendly open source tool rhizoTrak.
Methods and results: rhizoTrak builds on TrakEM2 and is publicly available as Fiji plugin. It uses treelines to represent branching structures in roots and assigns customizable status labels per root segment. rhizoTrak offers configuration options for visualization and various functions for root annotation mostly accessible via keyboard shortcuts. rhizoTrak allows time-series data import and particularly supports easy handling and annotation of time-series images. This is facilitated via explicit temporal links (connectors) between roots which are automatically generated when copying annotations from one image to the next. rhizoTrak includes automatic consistency checks and guided procedures for resolving inconsistencies. It facilitates easy data exchange with other software by supporting open data formats.
Conclusions: rhizoTrak covers the full range of functions required for user-friendly and efficient annotation of time-series images. Its flexibility and open source nature will foster efficient data acquisition procedures in root studies using minirhizotrons.},
  issn = {1573-5036},
  doi = {10.1007/s11104-019-04199-3},
  url = {https://doi.org/10.1007/s11104-019-04199-3}
}
@incollection{Moeller19_BPCM_cytoskeleton,
  author = {M{\"o}ller, Birgit and Zergiebel, Luise and B{\"u}rstenbinder, Katharina},
  editor = {Cvr{\v{c}}kov{\'a}, Fatima and {\v{Z}}{\'a}rsk{\'y}, Viktor},
  title = {Quantitative and Comparative Analysis of Global Patterns of (Microtubule) Cytoskeleton Organization with CytoskeletonAnalyzer2D},
  booktitle = {Plant Cell Morphogenesis: Methods and Protocols},
  chapter = {10},
  year = {2019},
  publisher = {Springer New York},
  address = {New York, NY},
  pages = {151--171},
  abstract = {The microtubule cytoskeleton plays important roles in cell morphogenesis. To investigate the mechanisms of cytoskeletal organization, for example, during growth or development, in genetic studies, or in response to environmental stimuli, image analysis tools for quantitative assessment are needed. Here, we present a method for texture measure-based quantification and comparative analysis of global microtubule cytoskeleton patterns and subsequent visualization of output data. In contrast to other approaches that focus on the extraction of individual cytoskeletal fibers and analysis of their orientation relative to the growth axis, CytoskeletonAnalyzer2D quantifies cytoskeletal organization based on the analysis of local binary patterns. CytoskeletonAnalyzer2D thus is particularly well suited to study cytoskeletal organization in cells where individual fibers are difficult to extract or which lack a clearly defined growth axis, such as leaf epidermal pavement cells. The tool is available as ImageJ plugin and can be combined with publicly available software and tools, such as R and Cytoscape, to visualize similarity networks of cytoskeletal patterns.},
  isbn = {978-1-4939-9469-4},
  doi = {10.1007/978-1-4939-9469-4_10},
  url = {https://doi.org/10.1007/978-1-4939-9469-4_10}
}
@incollection{Moeller19_BPCM_pacequant,
  author = {M{\"o}ller, Birgit and Poeschl, Yvonne and Klemm, Sandra and B{\"u}rstenbinder, Katharina},
  editor = {Cvr{\v{c}}kov{\'a}, Fatima and {\v{Z}}{\'a}rsk{\'y}, Viktor},
  title = {Morphological Analysis of Leaf Epidermis Pavement Cells with PaCeQuant},
  booktitle = {Plant Cell Morphogenesis: Methods and Protocols},
  chapter = {22},
  year = {2019},
  publisher = {Springer New York},
  address = {New York, NY},
  pages = {329--349},
  abstract = {Morphological analysis of cell shapes requires segmentation of cell contours from input images and subsequent extraction of meaningful shape descriptors that provide the basis for qualitative and quantitative assessment of shape characteristics. Here, we describe the publicly available ImageJ plugin PaCeQuant and its associated R package PaCeQuantAna, which provides a pipeline for fully automatic segmentation, feature extractionFeature extraction, statistical analysis, and graphical visualization of cell shape properties. PaCeQuant is specifically well suited for analysis of jigsaw puzzle-like leaf epidermis pavement cells from 2D input images and supports the quantification of global, contour-based, skeleton-based, and pavement cell-specific shape descriptors.},
  isbn = {978-1-4939-9469-4},
  doi = {10.1007/978-1-4939-9469-4_22},
  url = {https://doi.org/10.1007/978-1-4939-9469-4_22}
}
@inproceedings{Moeller19_ISBI,
  title = {Semi-automatic Cell Segmentation from Noisy Image Data for Quantification of Microtubule Organization on Single Cell Level},
  author = {B.~M{\"o}ller and K.~B{\"u}rstenbinder},
  booktitle = {Proc. of IEEE 16th International Symposium on Biomedical Imaging (ISBI)},
  year = {2019},
  address = {Venice, Italy},
  month = {April},
  pages = {199-203},
  isbn = {978-1-5386-3640-4},
  abstract = {The structure of the microtubule cytoskeleton provides valuable information related to morphogenesis of cells. The cytoskeleton organizes into diverse patterns that vary in cells of different types and tissues, but also within a single tissue. To assess differences in cytoskeleton organization methods are needed that quantify cytoskeleton patterns within a complete cell and which are suitable for large data sets. A major bottleneck in most approaches, however, is a lack of techniques for automatic extraction of cell contours. Here, we present a semi-automatic pipeline for cell segmentation and quantification of microtubule organization. Automatic methods are applied to extract major parts of the contours and a handy image editor is provided to manually add missing information efficiently. Experimental results prove that our approach yields high-quality contour data with minimal user intervention and serves a suitable basis for subsequent quantitative studies.},
  keywords = {Image segmentation;Organizations;Data mining;Feature extraction;Noise measurement;Pipelines;Standards organizations;cytoskeleton;cell segmentation;vesselness;gap closing;label editor;texture;clustering;ImageJ},
  doi = {10.1109/ISBI.2019.8759145},
  issn = {1945-8452},
  month = {April},
  url = {https://ieeexplore.ieee.org/document/8759145}
}
@inproceedings{Moeller19_Bioimaging,
  title = {{Q}uantification of {S}tromule {F}requencies in {M}icroscope {I}mages of {P}lastids combining {R}idge {D}etection and {G}eometric {C}riteria},
  author = {B.~M{\"o}ller and M.~Schattat},
  booktitle = {Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING,},
  year = {2019},
  pages = {38-48},
  publisher = {SciTePress},
  organization = {INSTICC},
  doi = {10.5220/0007390300380048},
  url = {https://www.scitepress.org/PublicationsDetail.aspx?ID=H1fepfq9NBw=&t=1},
  isbn = {978-989-758-353-7},
  month = {February},
  address = {Prague, Czech Republic},
  abstract = {Plastids are involved in many fundamental biochemical pathways in plants. They can produce tubular membrane out-folds from their surface. These so-called stromules have initially been described over a century ago, but their functional role is still elusive. To identify cellular processes or genetic elements underlying stromule formation screens of large populations of mutant plants or plants under different treatments are carried out and stromule frequencies are extracted. Due to a lack of automatic methods, however, this quantification is usually done manually rendering this step a main bottleneck in stromule research. Here, we present a new approach for quantification of stromule frequencies. Plastids are extracted from microscope images using local wavelet analysis over multiple scales combined with statistical hypothesis testing to resolve competing detections from different scales. Subsequently, for each plastid region evidence for the existence of stromules in its vicinity is investigated applying ridge detection techniques and geometric criteria. Experimental results prove that our approach is suitable to properly identify stromules. Even in microscopy images with a high noise level and distracting signals extracted stromule counts are comparable to those of biological experts.}
}
@article{Moeller19_JEB,
  author = {Mitra, Dipannita and Klemm, Sandra and Kumari, Pratibha and Quegwer, Jakob and Möller, Birgit and Poeschl, Yvonne and Pflug, Paul and Stamm, Gina and Abel, Steffen and Bürstenbinder, Katharina},
  title = {Microtubule-associated protein IQ67 DOMAIN5 regulates morphogenesis of leaf pavement cells in Arabidopsis thaliana},
  journal = {Journal of Experimental Botany},
  volume = {70},
  number = {2},
  pages = {529-543},
  year = {2019},
  doi = {10.1093/jxb/ery395},
  url = {http://dx.doi.org/10.1093/jxb/ery395},
  eprint = {https://www.biorxiv.org/content/biorxiv/early/2018/02/20/268466.full-text.pdf},
  abstract = {Plant microtubules form a highly dynamic intracellular network with important roles for regulating cell division, cell proliferation, and cell morphology. Their organization and dynamics are co-ordinated by various microtubule-associated proteins (MAPs) that integrate environmental and developmental stimuli to fine-tune and adjust cytoskeletal arrays. IQ67 DOMAIN (IQD) proteins recently emerged as a class of plant-specific MAPs with largely unknown functions. Here, using a reverse genetics approach, we characterize Arabidopsis IQD5 in terms of its expression domains, subcellular localization, and biological functions. We show that IQD5 is expressed mostly in vegetative tissues, where it localizes to cortical microtubule arrays. Our phenotypic analysis of iqd5 loss-of-function lines reveals functions of IQD5 in pavement cell (PC) shape morphogenesis. Histochemical analysis of cell wall composition further suggests reduced rates of cellulose deposition in anticlinal cell walls, which correlate with reduced anisotropic expansion. Lastly, we demonstrate IQD5-dependent recruitment of calmodulin calcium sensors to cortical microtubule arrays and provide first evidence for important roles for calcium in regulation of PC morphogenesis. Our work identifies IQD5 as a novel player in PC shape regulation and, for the first time, links calcium signaling to developmental processes that regulate anisotropic growth in PCs.}
}
@inproceedings{Moeller18_EMBL-01,
  title = {{A}nalysis of {C}ell {M}orphology with the {I}mage{J} {P}lugin {P}a{C}e{Q}uant},
  author = {B.~M{\"o}ller and Y.~Poeschl and K.~B{\"u}rstenbinder},
  booktitle = {EMBL Conference: From Images to Knowledge with ImageJ \& Friends},
  year = {2018},
  address = {EMBL Heidelberg, Germany},
  month = {December},
  note = {Poster Presentation}
}
@inproceedings{Moeller18_EMBL-02,
  title = {{M}inirhizotron {I}mage {A}nnotation in {F}iji with rhizo{T}rak},
  author = {B.~M{\"o}ller and H.~Chen and T.~Schmidt and A.~Zieschank and R.~Patzak and B.~Schreck and M.~T{\"u}rke and A.~Weigelt and S.~Posch},
  booktitle = {EMBL Conference: From Images to Knowledge with ImageJ \& Friends},
  year = {2018},
  address = {EMBL Heidelberg, Germany},
  month = {December},
  note = {Poster Presentation}
}
@article{Moeller17_PPhys,
  title = {{P}a{C}e{Q}uant: {A} {T}ool for {H}igh-{T}hroughput {Q}uantification of {P}avement {C}ell {S}hape {C}haracteristics},
  author = {Birgit M{\"o}ller and Yvonne Poeschl and Romina Pl{\"o}tner and Katharina B{\"u}rstenbinder},
  journal = {Plant Physiology},
  year = {2017},
  month = {November},
  number = {3},
  pages = {998--1017},
  volume = {175},
  abstract = {Pavement cells (PCs) are the most frequently occurring cell type in the leaf epidermis and play important roles in leaf growth and function. In many plant species, PCs form highly complex jigsaw-puzzle-shaped cells with interlocking lobes. Understanding of their development is of high interest for plant science research because of their importance for leaf growth and hence for plant fitness and crop yield. Studies of PC development, however, are limited, because robust methods are lacking that enable automatic segmentation and quantification of PC shape parameters suitable to reflect their cellular complexity. Here, we present our new ImageJ-based tool, PaCeQuant, which provides a fully automatic image analysis workflow for PC shape quantification. PaCeQuant automatically detects cell boundaries of PCs from confocal input images and enables manual correction of automatic segmentation results or direct import of manually segmented cells. PaCeQuant simultaneously extracts 27 shape features that include global, contour-based, skeleton-based, and PC-specific object descriptors. In addition, we included a method for classification and analysis of lobes at two-cell junctions and three-cell junctions, respectively. We provide an R script for graphical visualization and statistical analysis. We validated PaCeQuant by extensive comparative analysis to manual segmentation and existing quantification tools and demonstrated its usability to analyze PC shape characteristics during development and between different genotypes. PaCeQuant thus provides a platform for robust, efficient, and reproducible quantitat
  doi = {10.1104/pp.17.00961},
  file = {:http\://www.plantphysiol.org/content/175/3/998.full.pdf:URL},
  owner = {moeller},
  timestamp = {2017.09.22},
  url = {http://www.plantphysiol.org/content/175/3/998}
}
@article{Posch17_JORS,
  title = {Alida - {A}dvanced {L}ibrary for {I}ntegrated {D}evelopment of {D}ata {A}nalysis {A}pplications},
  author = {Stefan Posch and Birgit M{\"o}ller},
  journal = {Journal of Open Research Software},
  year = {2017},
  number = {1},
  pages = {7},
  volume = {5},
  abstract = {Data analysis procedures can often be modeled as a set of manipulation operations applied to input data and resulting in transformed intermediate and result data. The Java library Alida is providing an advanced development framework to support programmers in developing data analysis applications adhering to such a scheme. The main intention of Alida is to foster re-usability by offering well-defined, unified, modular APIs and execution procedures for operators, and to ease development by releasing developers from tedious tasks. Alida features automatic generation of handy graphical and command line user interfaces, a built-in graphical editor for workflow design, and an automatic documentation of analysis pipelines. Alida is available from its project webpage http://www.informatik.uni-halle.de/alida, on Github and via our Maven server.},
  doi = {http://doi.org/10.5334/jors.124},
  keywords = {Data Analysis,  Programming Framework,  Implementation,  Reusability,  Graphical User Interfaces,  Command Line Interface,  Processing History,  Java Software Library},
  owner = {moeller},
  timestamp = {2017.02.13},
  url = {http://openresearchsoftware.metajnl.com/articles/10.5334/jors.124/}
}
@article{Buerste17_PPhys,
  title = {{T}he {IQD} {F}amily of {C}almodulin-{B}inding {P}roteins {L}inks {C}alcium {S}ignaling to {M}icrotubules, {M}embrane {S}ubdomains, and the {N}ucleus},
  author = {Katharina B{\"u}rstenbinder and Birgit M{\"o}ller and Romina Pl{\"o}tner and Gina Stamm and Gerd Hause and Dipannita Mitra and Steffen Abel},
  journal = {Plant Physiology},
  year = {2017},
  volume = {173},
  number = {3},
  month = {March},
  pages = {1692-1708},
  abstract = {Calcium (Ca2+) signaling and dynamic reorganization of the cytoskeleton are essential processes for the coordination and control of plant cell shape and cell growth. Calmodulin (CaM) and closely related calmodulin-like (CML) polypeptides are principal sensors of Ca2+ signals. CaM/CMLs decode and relay information encrypted by the second messenger via differential interactions with a wide spectrum of targets to modulate their diverse biochemical activities. The plant-specific IQ67 DOMAIN (IQD) family emerged as possibly the largest class of CaM-interacting proteins with undefined molecular functions and biological roles. Here, we show that the 33 members of the IQD family in Arabidopsis (Arabidopsis thaliana) differentially localize, using green fluorescent protein (GFP)-tagged proteins, to multiple and distinct subcellular sites, including microtubule (MT) arrays, plasma membrane subdomains, and nuclear compartments. Intriguingly, the various IQD-specific localization patterns coincide with the subcellular patterns of IQD-dependent recruitment of CaM, suggesting that the diverse IQD members sequester Ca2+-CaM signaling modules to specific subcellular sites for precise regulation of Ca2+-dependent processes. Because MT localization is a hallmark of most IQD family members, we quantitatively analyzed GFP-labeled MT arrays in Nicotiana benthamiana cells transiently expressing GFP-IQD fusions and observed IQD-specific MT patterns, which point to a role of IQDs in MT organization and dynamics. Indeed, stable overexpression of select IQD proteins in Arabidopsis altered cellular MT orientation, cell shape, and organ morphology. Because IQDs share biochemical properties with scaffold proteins, we propose that IQD families provide an assortment of platform proteins for integrating CaM-dependent Ca2+ signaling at multiple cellular sites to regulate cell function, shape, and growth.},
  doi = {10.1104/pp.16.01743},
  url = {https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5338658/#}
}
@article{Moeller16_JORS,
  title = {MiToBo - A Toolbox for Image Processing and Analysis},
  author = {Birgit M{\"o}ller and Markus Gla{\ss} and Danny Misiak and Stefan Posch},
  journal = {Journal of Open Research Software},
  year = {2016},
  number = {1},
  pages = {e17},
  volume = {4},
  abstract = {MiToBo is a toolbox and Java library for solving basic as well as advanced image processing and analysis tasks. It features a rich collection of fundamental, intermediate and high-level image processing operators and algorithms as well as a couple of sophisticated tools for specific biological and biomedical applications. These tools include operators for elucidating cellular morphology and locomotion as well as operators for the characterization of certain intracellular particles and structures.

MiToBo builds upon and integrates into the widely-used image analysis software packages ImageJ and Fiji [11, 10], and all of its operators can easily be run in ImageJ and Fiji via a generic operator runner plugin. Alternatively MiToBo operators can directly be run from command line, and using its functionality as a library for developing own applications is also supported. Thanks to the Alida library [8] forming the base of MiToBo all operators share unified APIs fostering reusability, and graphical as well as command line user interfaces for operators are automatically generated. MiToBo is available from its website http://www.informatik.uni-halle.de/mitobo, on Github, via an Apache Archiva Maven repository server, and it can easily be activated in Fiji via its own update site.},
  doi = {http://dx.doi.org/10.5334/jors.103},
  file = {:http\://openresearchsoftware.metajnl.com/articles/10.5334/jors.103/galley/153/download/:URL},
  keywords = {Image Analysis,  Image Processing,  Toolbox,  Java Library,  ImageJ,  Fiji,  Microscope Images,  Biomedical Imaging,  Wound Closure,  Actin Microfilament,  Morphology,  Protein Profile},
  url = {http://openresearchsoftware.metajnl.com/articles/10.5334/jors.103/}
}
@article{Posch16_JPRIA,
  title = {Design and implementation of the Alida framework to ease the development of image analysis algorithms},
  author = {Posch, S. and M{\"o}ller, B.},
  journal = {Pattern Recognition and Image Analysis},
  year = {2016},
  number = {1},
  pages = {181--189},
  volume = {26},
  abstract = {Solving image analysis problems is not restricted to the pure delineation of algorithms suitable to tackle the task at hand. Rather these also need to be made available to the users promptly and equipped with handy user interfaces to foster progress in the intended field of application. Alida is a software framework to advance the integrated development of algorithms and appropriate user interfaces. It automatically generates user interfaces for implemented algorithms, offers an automatic documentation of analysis procedures, and ships with a graphical editor for designing complex workflows. Alida's Java implementation is licensed under GPL 3.0 and publicly available at http://www.informatik.uni-halle.de/alida.},
  doi = {10.1134/S105466181601020X},
  issn = {1555-6212},
  keywords = {image analysis, user interface, process documentation, workflow design, software development},
  url = {http://dx.doi.org/10.1134/S105466181601020X}
}
@article{Franke15_JECR,
  title = {{T}he '{MTB} {C}ell {C}ounter' a versatile tool for the semi-automated quantification of sub-cellular phenotypes in fluorescence microscopy images. {A} case study on plastids, nuclei and peroxisomes},
  author = {Lars Franke and Benjamin Storbeck and Jessica Lee Erickson and Daniela R{\"o}del and Daniel Schr{\"o}ter and Birgit M{\"o}ller and Martin Hartmut Schattat},
  journal = {Journal of Endocytobiosis and Cell Research},
  year = {2015},
  pages = {31-42},
  volume = {26},
  abstract = {Organelle morphology as well as subcellular organisation can drastically change in response to a changing cellular environment. However our knowledge about the functionality as well as the regulation of organelle form changes, such as plastid tubule formation (stromules) and organelle rearrangements, is limited. Monitoring changes to organelle morphology and subcellular organisation in response to experimental treatments and in different mutant backgrounds is a promising strategy to address open questions. However, for a detailed comparison of different treatments and mutants, the quantification of subcellular phenotypes is crucial. Unfortunately, for many specific subcellular parameters, such as stromule frequency, software tools supporting data extraction from images are not readily available or are highly specialized in their purpose. In order to quantify stromule frequency in a semi-automated manner we developed the 'MTB Cell Counter', which combines automated plastid detection with manual counting tools. We show that with the use of our plugin stromule frequency can be quantified up to 90% faster. We further demonstrate, with the detection of peroxisomes and nuclei, that due to its adaptable detection algorithm, which is based on scale-adaptive analysis of wavelet coefficients, the plugin can be used to reliably detect and count organelles of different size and brightness. In addition to the analysis of CLSM images, the 'MTB Cell Counter' is easily adapted to particle detection in challenging epifluorescence images, making it a versatile, semi-automated tool capable of quantifying a wide variety of subcellular phenotypes.},
  file = {:http\://zs.thulb.uni-jena.de/servlets/MCRFileNodeServlet/jportal_derivate_00242396/ECR_2015_31-42_Franke.etal..pdf:PDF},
  keywords = {plastid, nucleus, peroxisome, image analysis, ImageJ, MiToBo, stromule, cell biology},
  owner = {moeller},
  timestamp = {2015.06.17},
  url = {http://zs.thulb.uni-jena.de/receive/jportal_jparticle_00342296}
}
@inproceedings{Posch14_OGRW,
  title = {{D}esign and {I}mplementation of the {A}lida {F}ramework to {E}ase the {D}evelopment of {I}mage {A}nalysis {A}lgorithms},
  author = {Stefan Posch and Birgit M{\"o}ller},
  booktitle = {9th Open German-Russian Workshop on Pattern Recognition and Image Understanding ({OGRW} 2014), Proceedings},
  year = {2015},
  address = {Koblenz},
  editor = {Dietrich Paulus and Christian Fuchs and Detlev Droege},
  month = {5},
  note = {Workshop Chairs: Heinrich Niemann, Yuri Zhuravlev},
  pages = {75-81},
  publisher = {University of Koblenz-Landau},
  abstract = {Solving image analysis problems is not restricted to the pure delineation of algorithms suitable to tackle the task at hand. Rather these also need to be made available to the users promptly and equipped with handy user interfaces to foster progress in the intended field of application. Alida is a software framework to advance the integrated development of algorithms and appropriate user interfaces. It automatically generates user interfaces for implemented algorithms, offers an automatic documentation of analysis procedures, and ships with a graphical editor for designing complex workflows. Alida s Java implementation is licensed under GPL 3.0 and publicly available at http://www.informatik.uni-halle.de/alida.},
  file = {:http\://kola.opus.hbz-nrw.de/volltexte/2015/1136/pdf/OGRW_2014_Proceedings.pdf:URL},
  shorttitle = {{OGRW}},
  url = {http://kola.opus.hbz-nrw.de/volltexte/2015/1136/pdf/OGRW_2014_Proceedings.pdf#82},
  urn = {urn:nbn:de:hbz:kob7-2015051206}
}
@article{Bley15_NAR,
  title = {Stress granules are dispensable for {mRNA} stabilization during cellular stress},
  author = {N. Bley and M. Lederer and B. Pfalz and C. Reinke and T. Fuchs and M. Gla{\ss} and B. M{\"o}ller and S. H{\"u}ttelmaier},
  journal = {Nucleic Acids Research},
  year = {2015},
  month = {February},
  note = {PubMed ID: 25488811, PubMed CID: PMC4344486},
  number = {4},
  pages = {e26},
  volume = {43},
  abstract = {During cellular stress, protein synthesis is severely reduced and bulk mRNA is recruited to stress granules (SGs). Previously, we showed that the SG-recruited IGF2 mRNA-binding protein 1 (IGF2BP1) interferes with target mRNA degradation during cellular stress. Whether this requires the formation of SGs remained elusive. Here, we demonstrate that the sustained inhibition of visible SGs requires the concomitant knockdown of TIA1, TIAR and G3BP1. FRAP and photo-conversion studies, however, indicate that these proteins only transiently associate with SGs. This suggests that instead of forming a rigid scaffold for mRNP recruitment, TIA proteins and G3BP1 promote SG-formation by constantly replenishing mRNPs. In contrast, RNA-binding proteins like IGF2BP1 or HUR, which are dispensable for SG-assembly, are stably associated with SGs and the IGF2BP1/HUR-G3BP1 association is increased during stress. The depletion of IGF2BP1 enhances the degradation of target mRNAs irrespective of inhibiting SG-formation, whereas the turnover of bulk mRNA remains unaffected when SG-formation is impaired. Together these findings indicate that the stabilization of mRNAs during cellular stress is facilitated by the formation of stable mRNPs, which are recruited to SGs by TIA proteins and/or G3BP1. Importantly, however, the aggregation of mRNPs to visible SGs is dispensable for preventing mRNA degradation.},
  doi = {10.1093/nar/gku1275},
  timestamp = {2014.02.04},
  url = {http://nar.oxfordjournals.org/content/43/4/e26.long}
}
@inproceedings{Moeller14_ICPR,
  author = {B. M{\"o}ller and E. Piltz and N. Bley},
  title = {Quantification of Actin Structures using Unsupervised Pattern Analysis Techniques},
  booktitle = {Proceedings of 22nd Int.~Conf.~on Pattern Recognition (ICPR)},
  year = {2014},
  pages = {3251-3256},
  address = {Stockholm, Sweden},
  month = {August},
  publisher = {IEEE},
  abstract = {The analysis of F-actin organization in cells is a
key topic in many fields of biomedical research. While standard
protocols for imaging immunostained actin are well established,
assessment of the resulting microscopy images is most of the time
still performed manually and with a high degree of subjectivity.
In this paper, we present a new approach for the analysis of
actin structures in microscopy images and the quantification of
differences and similarities in actin organization between cells.
Compared to existing methods, our approach does not require any
previous knowledge about the cells or structures to be analyzed.
It works in an unsupervised fashion, combining statistical texture
measures and clustering techniques. By this, our method yields
large flexibility and allows for application in a wide range of ex-
perimental scenarios, and also to heterogeneous cell populations.
Experimental evaluation on sample data proves that our method
yields meaningful results for biomedical investigations.},
  keywords = {cellular biophysics;medical image processing;molecular biophysics;molecular configurations;pattern clustering;proteins;statistical analysis;F-actin organization analysis;actin structure quantification;biomedical investigation;biomedical research;cell biology;clustering techniques;heterogeneous cell populations;imaging immunostained actin;microscopy images;statistical texture;unsupervised pattern analysis;Feature extraction;Image segmentation;Microscopy;Organizations;Sociology;Statistics;Vectors;actin structures;clustering;quantification;texture},
  doi = {10.1109/ICPR.2014.560},
  issn = {1051-4651},
  url = {http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6977272&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6977272}
}
@article{Misiak14_JNM,
  author = {Danny Misiak and Stefan Posch and Marcell Lederer and Claudia Reinke
        and Stefan H{\"u}ttelmaier and Birgit M{\"o}ller},
  title = {Extraction of protein profiles from primary neurons using active
        contour models and wavelets},
  journal = {Journal of Neuroscience Methods},
  year = {2014},
  volume = {225},
  pages = {1-12},
  month = {March},
  abstract = {The function of complex networks in the nervous system relies on the
        proper formation of neuronal contacts and their remodeling. To decipher
        the molecular mechanisms underlying these processes, it is essential
        to establish unbiased automated tools allowing the correlation of
        neurite morphology and the subcellular distribution of molecules
        by quantitative means.
        
        
        We developed NeuronAnalyzer2D, a plugin for ImageJ, which allows the
        extraction of neuronal cell morphologies from two dimensional high
        resolution images, and in particular their correlation with protein
        profiles determined by indirect immunostaining of primary neurons.
        The prominent feature of our approach is the ability to extract subcellular
        distributions of distinct biomolecules along neurites. To extract
        the complete areas of neurons, required for this analysis, we employ
        active contours with a new distance based energy. For locating the
        structural parts of neurons and various morphological parameters
        we adopt a wavelet based approach. The presented approach is able
        to extract distinctive profiles of several proteins and reports detailed
        morphology measurements on neurites.

        We compare the detected neurons from NeuronAnalyzer2D with those obtained
        by NeuriteTracer and Vaa3D-Neuron, two popular tools for automatic
        neurite tracing. The distinctive profiles extracted for several proteins,
        for example, of the mRNA binding protein ZBP1, and a comparative
        evaluation of the neuron segmentation results proves the high quality
        of the quantitative data and proves its practical utility for biomedical
        analyses.},
  doi = {http://dx.doi.org/10.1016/j.jneumeth.2013.12.009},
  keywords = {Active contours; Fluorescence microscopy; High-content analysis; Neuron
        morphology; Protein distribution; Segmentation;
        
            Wavelets},
  url = {http://www.sciencedirect.com/science/article/pii/S0165027013004330}
}

@inproceedings{Moeller13_IbPRIA,
  author = {Armagan Elibol and Stefan Posch and Andreas Maurer and Klaus Pillen
        and Birgit M{\"o}ller},
  title = {Vision-based 3D-Reconstruction of Barley Plants},
  booktitle = {Proc. of 6th Iberian Conference on Pattern Recognition and Image
        Analysis},
  year = {2013},
  pages = {406-415},
  address = {Madeira, Portugal},
  month = {June},
  abstract = {For multi-view 3D reconstruction robust standard procedures have been
        established and can directly be applied to many scenarios. However,
        the extraction of point correspondences as a prerequisite for reconstruction
        is demanding for various applications. Here we present a new analysis
        pipeline for 3D reconstruction in the field of barley plant monitoring.
        Barley plants show a significant structural and textural similarity
        rendering the application of standard procedures to extract correspondences
        impossible. Our new approach overcomes these problems by combining
        information from various cues over different stages. Experiments
        on real data prove the suitability of our approach to generate 3D
        models of the plants from which phenotypical data can easily be derived.},
  bibsource = {DBLP, http://dblp.uni-trier.de},
  ee = {http://dx.doi.org/10.1007/978-3-642-38628-2_48}
}
@inproceedings{Moeller13_MVA,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {A Framework Unifying the Development of Image Analysis Algorithms
        and Associated User Interfaces},
  booktitle = {Proc. of 13th IAPR International Conference on Machine Vision Applications
        (MVA)},
  year = {2013},
  address = {Kyoto, Japan},
  month = {May},
  pages = {447-450},
  abstract = {Solving image analysis problems not only requires the development of 
        suitable sets of algorithms to produce desired result data, but also demands 
        for suitable user interfaces (UIs) to foster use in practice. Here we present 
        our library Alida which aims to promote the deployment of UIs by featuring their 
        automatic generation from algorithm code. Alida supports command line and 
        graphical UIs (GUIs), and ships with a graphical editor for designing more complex 
        workflows. Enforcing only a small set of rules to obey Alida significantly reduces 
        implementation overhead for developers and allows for focusing on algorithm rather
        than UI design. The suitability of Alida’s concept for real-life applications is 
        shown by the library MiToBo for biomedical image analysis implemented based on Alida.}
}
@inproceedings{Elibol08_ISCIS,
  author = {A. Elibol and B. M{\"o}ller and R. Garcia},
  title = {Perspectives of Auto-Correcting Lens Distortions in Mosaic-Based
	Underwater Navigation"},
  booktitle = {Proc. of 23rd IEEE Int. Symposium on Computer and Information Sciences
	(ISCIS)},
  year = {2008},
  address = {Istanbul, Turkey},
  month = {October},
  publisher = {IEEE},
  abstract = {When unmanned underwater vehicles (UUVs) perform missions near the
	ocean floor, optical sensors can be used to improve local navigation.
	Video mosaics allow to efficiently process the images acquired by
	the vehicle, and also to obtain position estimates. We discuss in
	this paper the role of lens distortions in this context, proving
	that degenerate mosaics have their origin not only in the selected
	motion model or in registration errors, but also in the cumulative
	effect of radial distortion residuals. Additionally, we present results
	on the accuracy of different feature-based approaches for self-correction
	of lens distortions that may guide the choice of appropriate techniques
	for correcting distortions.},
  url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4717863}
}
@inproceedings{Glass12_ImageJ,
  author = {M. Gla{\ss} and B. M{\"o}ller and S. Posch},
  title = {Scratch Assay Analysis in ImageJ},
  booktitle = {Proc. of ImageJ User \& Developer Conference},
  year = {2012},
  pages = {211-214},
  address = {Mondorf-les-Bains, Luxembourg},
  month = {October},
  abstract = {Scratch assays are a widely used technique for assessing the migratory
	potential of cells. However, due to a lack of appropriate tools these assays 
        are often analyzed manually. Here we present a plugin for the automatic	
	segmentation and analysis of scratch assay images. The input images
	are segmented using a topology-preserving non-PDE level set approach. 
        To exclude images where the scratch has	already been completely closed a support	
	vector machine separates images containing a scratch from such that
	do not. As our method requires adjustment of only two parameters, 
        it is easy to use and has already been successfully applied in practice.},
  comment = {ISBN 2-919941-18-6},
  keywords = {Scratch assay, Level sets, SVM, Entropy, Topology preservation}
}
@inproceedings{Glass11_IbPRIA,
  author = {M. Gla{\ss} and B. M{\"o}ller and A. Zirkel and K. W{\"a}chter and
	S. H{\"u}ttelmaier and S. Posch},
  title = {Scratch Assay Analysis with Topology-preserving Level Sets and Texture
	Measures},
  booktitle = {Proc. of 5th Iberian Conference on Pattern Recognition and Image
	Analysis (IbPRIA '11)},
  year = {2011},
  editor = {Jordi Vitri{\`a} and Jo{\~a}o M. Sanches and Mario Hern{\'a}ndez},
  number = {6669},
  series = {LNCS},
  pages = {100-108},
  address = {Gran Canaria, Spain},
  publisher = {Springer},
  abstract = {Scratch assays are widely used for cell motility and migration assessment
	in biomedical research. However, quantitative data is very often
	extracted manually. Here, we present a fully automated analysis pipeline
	for detecting scratch boundaries and measuring areas in scratch assay
	images based on level set techniques. In particular, non-PDE level
	sets are extended for topology preservation and applied to entropy
	data of scratch assay microscope images. Compared to other algorithms
	our approach, implemented in Java as ImageJ plugin based on the extension
	package MiToBo, relies on a minimal set of configuration parameters.
	Experimental evaluations show the high-quality of extracted assay
	data and their suitability for biomedical investigations.},
  doi = {10.1007/978-3-642-21257-4},
  keywords = {Scratch assay, level set segmentation, texture, topology},
  url = {http://www.springerlink.com/content/978-3-642-21256-7/#section=910893&page=1&locus=0}
}
@article{Glass12_PR,
  author = {M. Gla{\ss} and B. M{\"o}ller and A. Zirkel and K. W{\"a}chter and
	S. H{\"u}ttelmaier and S. Posch},
  title = {Cell Migration Analysis: Segmenting Scratch Assay Images with Level
	Sets and Support Vector Machines},
  journal = {Pattern Recognition},
  year = {2012},
  volume = {45},
  pages = {3154-3165},
  number = {9},
  month = {September},
  abstract = {Cell migration assessment is often done by scratch assay experiments
	for which quantitative evaluations are usually performed manually.
	Here we present an automatic analysis pipeline detecting scratch
	boundaries and measuring areas based on level sets. We extend non-PDE
	level sets for topology-preservation and use an entropy-based energy
	functional. This approach by design segments a scratch in every image,
	hence, we employ support vector machines to identify images showing
	no scratch at all. Compared to other algorithms our approach, implemented
	as ImageJ plugin, relies on a minimal set of parameters. Experimental
	evaluations show the high quality of results and their suitability
	for biomedical investigations.},
  doi = {10.1016/j.patcog.2012.03.001},
  keywords = {Scratch assay, Segmentation, Level sets, Texture, Topology, SVM},
  url = {http://www.sciencedirect.com/science/article/pii/S0031320312001173}
}
@inproceedings{Gress10_BVM,
  author = {Oliver Gre{\ss} and Birgit M{\"o}ller and Nadine St{\"o}hr and Stefan
	H{\"u}ttelmaier and Stefan Posch},
  title = {Scale-adaptive Wavelet-based Particle Detection in Microscopy Images},
  booktitle = {{Bildverarbeitung f{\"u}r die Medizin}},
  year = {2010},
  editor = {Hans-Peter Meinzer and Thomas Martin Deserno and Heinz Handels and
	Thomas Tolxdorff},
  series = {Informatik Aktuell},
  pages = {266-270},
  address = {Berlin},
  publisher = {Springer},
  note = {ISBN 978-3-642-11967-5},
  abstract = {Stress granules and processing bodies play a major role in analysing
	the physiology of cells under various environmental conditions. We
	present a fully automatic approach to detect such particles in fluorescence
	labeled microscope images. The detection is based on scale-adaptive
	analysis of wavelet coefficients allowing for an accurate detection
	of particles with a large variety in size. Results on real images
	illustrate the appropriateness of our approach and proof high quality.},
  location = {Aachen},
  url = {http://ceur-ws.org/Vol-574/bvm2010_54.pdf}
}
@inproceedings{Kirchner12_IJ,
  author = {S. Kirchner and S. Posch and B. M{\"o}ller},
  title = {Graphical Programming in Alida and ImageJ 2.0 with Grappa},
  booktitle = {Proc. of ImageJ User \& Developer Conference},
  year = {2012},
  pages = {138-143},
  address = {Mondorf-les-Bains, Luxembourg},
  month = {October},
  abstract = {Solving challenging image analysis problems usually requires to combine
	several individual analysis steps into comprehensive workflows. 
        To find a suitable combination of algorithms is often quite elaborate and accomplished
	interactively. In this paper we present our graphical program editor
	''Grappa'' (Graphical Program Editor for Alida) supporting the design of workflows 
        from individual image analysis operators in a graphical manner.
	Grappa is built on top of Alida and takes full advantage of Alida's
	operator annotation and generic execution mechanisms, as well as of its functionality
	to automatically generate graphical user interfaces for operators.
	Grappa is under active development and available as prototypical plugin
	for ImageJ and ImageJ 2.0.},
  comment = {ISBN 2-919941-18-6}
}
@inproceedings{Misiak09_GCB,
  author = {D. Misiak and S. Posch and N. St{\"o}hr and S. H{\"u}ttelmaier and
	B. M{\"o}ller},
  title = {Automatic Detection of Fluorescence Labeled Neurites in Microscope
	Images},
  booktitle = {German Conf. on Bioinformatics (GCB)},
  year = {2009},
  address = {Halle (Saale), Germany},
  month = {September},
  note = {Poster Presentation}
}
@inproceedings{Misiak09_WACV,
  author = {Danny Misiak and Stefan Posch and Nadine St{\"o}hr and Stefan H{\"u}ttelmaier
	and Birgit M{\"o}ller},
  title = {Automatic Analysis of Fluorescence Labeled Neurites in Microscope
	Images},
  booktitle = {IEEE Workshop on Applications of Computer Vision (WACV '09)},
  year = {2009},
  pages = {118-124},
  address = {Snowbird, Utah, USA},
  month = {December},
  publisher = {IEEE},
  note = {ISBN: 978-1-4244-5496-9, IEEE Catalog Number: CFP09082-CDR},
  abstract = {Microscope imaging technologies have turned out to yield an indispensable
	tool in modern biomedical research. Combined with fluorescence labeling
	techniques they not only provide new perspectives on tissues and
	cells as a whole, but also on processes at the cellular level, and
	will be one important experimental technique of systems biology.
	To handle this steadily increasing amount of image data, in this
	paper we propose a new and fully automatic approach for neurite segmentation
	and protein quantification. Our technique combines three phases of
	automatic neuron cell localization, neurite segmentation and protein
	analysis. In the second stage active contour models based on hierarchical
	Gradient Vector Flow fields are employed, enabling precise neurite
	segmentation despite inhomogeneous texture. Neurite segmentation
	results as well as protein quantification profiles from a set of
	test images demonstrate the appropriateness of our approach for practical
	biomedical research.},
  city = {Snowbird, Utah, USA},
  isbn = {978-1-4244-5496-9},
  url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=5403112&contentType=Conference+Publications&sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A5403027%29}
}
@phdthesis{Moeller05_PhD,
  author = {M{\"o}ller, B.},
  title = {Multi-Mosaikbilder - Ein Ansatz zur ikonischen Repr{\"a}sentation
	von Bilddaten aktiver Kameras},
  school = {Martin-Luther-Universit{\"a}t Halle-Wittenberg},
  year = {2005},
  abstract = {Die Dissertation stellt das neue Konzept der so genannten Multi-Mosaikbilder
	zur effizienten Repr{\"a}sentation von Bildsequenzen aktiver Kameras
	vor. Das Konzept zielt darauf ab, interaktiven Systemen ein visuelles
	Ged{\"a}chtnis f{\"u}r ikonische Daten zur Verf{\"u}gung zu stellen,
	das eine flexiblere Nutzung visueller Informationen erlaubt und damit
	zu einer Erh{\"o}hung der Leistungsf{\"a}higkeit und einer Verbesserung
	der Kommunikationsm{\"o}glichkeiten interaktiver Systeme beitragen
	kann.
	
	Mosaikbilder sind ein Mechanismus, der eine kompakte Darstellung von
	Bildfolgen erm{\"o}glicht. Dabei werden alle Bilder einer Folge unter
	Eliminierung redundanter Anteile und einer signifikanten Reduktion
	des Datenvolumens zu einem Bild verschmolzen. Der Einsatz existierender
	Verfahren zur Mosaikbildberechnung in interaktiven Systemen ist allerdings
	h{\"a}ufig aufgrund der verwendeten Koordinatensysteme und der gew{\"a}hlten
	Verarbeitungsstrategien mit Schwierigkeiten verbunden. Das neue Konzept
	der Multi-Mosaikbilder erweitert und erg{\"a}nzt daher g{\"a}ngige
	Ans{\"a}tze, um einen Einsatz dieser Techniken auch in ressourcenbeschr{\"a}nkten,
	interaktiven Systemen zu erm{\"o}glichen.
	
	Das neue Konzept gr{\"u}ndet im Kern auf der Verwendung polyedrischer
	Koordinaten, in denen Bilddaten station{\"a}rer rotierender Kameras
	weitgehend verzerrungsfrei repr{\"a}sentiert werden k{\"o}nnen. Gleichzeitig
	wird die direkte Anwendung existierender Bildverarbeitungsalgorithmen
	auf die Bilddaten erm{\"o}glicht. Dies gew{\"a}hrleistet einen einfachen
	Zugriff auf die gespeicherten Informationen und erlaubt interaktiven
	Systemen einen flexiblen Umgang mit der Datenstruktur. Dar{\"u}ber
	hinaus unterst{\"u}tzt das neue Konzept eine inkrementelle Online-Berechnung
	der Mosaikbilder, die Verarbeitung von Bildfolgen mit statischen
	und dynamischen Inhalten, und die ad{\"a}quate Darstellung von Bilddaten
	mit verschiedenen Zoomstufen innerhalb einer Aufl{\"o}sungshierarchie.
	
	Die praktische Relevanz des entwickelten Konzeptes wurde durch die
	Realisierung einer aktiven Szenenexploration auf Basis der Multi-Mosaikbilder
	belegt, die den Kreislauf aus Datenrepr{\"a}sentation und aktiver
	Akquisition schlie{\ss}t. Au{\ss}erdem erfolgte eine prototypische
	Integration des visuellen Speichers in die Architektur des interaktiven,
	mobilen Roboters BIRON, dessen F{\"a}higkeiten zum Lernen und Wiedererkennen
	von Objekten auf diese Weise verbessert werden sollen.},
  keywords = {Visueller Speicher, Interaktive Systeme, Multi-Mosaikbilder, Polyeder,
	Online-Mosaikbildberechnung, Dynamische Szenen, Aktive Szenenexploration,
	Mensch-Roboter-Interaktion, Objektlernen},
  url = {http://sundoc.bibliothek.uni-halle.de/diss-online/05/05H124/index.htm}
}
@mastersthesis{Moeller01_Master,
  author = {Birgit M{\"o}ller},
  title = {Detektion von Bewegung bei der Berechnung von Mosaikbildern},
  school = {Universit{\"a}t Bielefeld, Technische Fakult{\"a}t, AG Angewandte
	Informatik},
  year = {2001},
  type = {Diploma Thesis},
  address = {Bielefeld, Germany},
  month = {March},
  url = {http://aiweb.techfak.uni-bielefeld.de/pubs/2007/detektion-von-bewegung-bei-der-berechnung-von-mosaikbildern}
}
@inproceedings{Moeller07_VISAPP,
  author = {Birgit M{\"o}ller and Rafael Garcia and Stefan Posch},
  title = {Towards Objective Quality Assessment of Image Registration Results},
  booktitle = {Proc. of International Conference on Computer Vision Theory and Applications
	(VISAPP '07)},
  year = {2007},
  pages = {233-240},
  address = {Barcelona, Spain},
  month = {March},
  abstract = {Geometric registration of visual images is a fundamental intermediate
	processing step in a wide variety of computer vision applications
	that deal with image sequence analysis. 2D motion recovery and mosaicing,
	3D scene reconstruction and also motion detection approaches strongly
	rely on accurate registration results. However, automatically assessing
	the overall quality of a registration is a challenging task. In particular,
	optimization criteria used in registration are not necessarily closely
	linked to the final quality of the result and often show a lack of
	local sensitivity. In this paper we present a new approach for an
	objective quality metric in 2D image registration. The proposed method
	is based on local structure analysis and facilitates voting-techniques
	for error pooling, leading to an objective measure that correlates
	well with the visual appearance of registered images. Since observed
	differences are furthermore classified in more detail according to
	various underlying error sources, the new measure not only yields
	a suitable base for objective quality assessment, but also opens
	perspectives towards an automatic and optimally adjusted correction
	of errors.}
}
@inproceedings{Moeller08_GCB,
  author = {B. M{\"o}ller and O. Gre{\ss} and S. Posch},
  title = {A Comparative Study of Robust Feature Detectors for 2D Electrophoresis
	Gel Image Registration},
  booktitle = {Proc. of German Conference on Bioinformatics (GCB)},
  year = {2008},
  editor = {Andreas Beyer and Michael Schroeder},
  volume = {P-136},
  series = {Lecture Notes in Informatics},
  pages = {138-147},
  address = {Dresden, Germany},
  month = {September},
  abstract = {In this study we consider the performance of different feature detectors
	used as the basis for the registration of images from two-dimensional
	gel electrophoresis. These are three spot detectors also used to
	identify proteins, and two domain independent keypoint detectors.
	We conduct a case study with images from a publically available data
	set which are synthetically distorted using thin plate splines. The
	performance is assessed by the repeatability score, the probability
	of an image structure to be detected in original and distorted images
	with reasonable localization accuracy.},
  url = {http://subs.emis.de/LNI/Proceedings/Proceedings136/article2249.html}
}
@inproceedings{Moeller11_ICVS,
  author = {Birgit M{\"o}ller and Oliver Gre{\ss} and Stefan Posch},
  title = {Knowing what happened - Automatic Documentation of Image Analysis
	Processes},
  booktitle = {Proceedings of 8th International Conference on Computer Vision Systems},
  year = {2011},
  editor = {J.L. Crowley and B.A. Draper and M. Thonnat},
  volume = {6962},
  series = {LNCS},
  pages = {1-10},
  address = {Sophia Antipolis, France},
  publisher = {Springer},
  abstract = {Proper archiving or later reconstruction and verification of results
	in data analysis requires thorough logging of all manipulative actions
	on the data and corresponding parameter settings. Unfortunately such
	documentation tasks often enforce extensive and error prone manual
	activities by the user. To overcome these problems we present Alida,
	an approach for fully automatic documentation of data analysis procedures.
	Based on an unified operator interface all operations on data including
	their sequence and configurations are registered during analysis.
	Subsequently these data are made explicit in XML graph representations
	yielding a suitable base for visual and analytic inspection. As example
	for the application of Alida in practice we present MiToBo, a toolbox
	for image analysis implemented on the basis of Alida and demonstrating
	the advantages of automatic documentation for image analysis procedures.},
  doi = {10.1007/978-3-642-23968-7_1},
  keywords = {automatic documentation, meta data, XML, processing graph, image analysis},
  url = {http://www.springerlink.com/content/m331u047758nn84l/}
}
@inbook{Moeller11_VISIGRAPP,
  chapter = {Adaptive Segmentation of Particles and Cells for Fluorescent Microscope
	Imaging},
  pages = {154-169},
  title = {VISIGRAPP 2010, Revised Selected Papers of Int. Joint Conf. on Computer
	Vision, Imaging and Computer Graphics. Theory and Applications},
  publisher = {Springer},
  year = {2011},
  editor = {P. Richard and J. Braz},
  author = {B. M{\"o}ller and O. Gre{\ss} and N. St{\"o}hr and S. H{\"u}ttelmaier
	and S. Posch},
  volume = {229},
  series = {Communications in Computer and Information Science},
  note = {ISBN 978-3-642-25381-2},
  abstract = {Analysis of biomolecules in cells essentially relies on fluorescence
	microscopy. In combination with fully automatic image analysis it
	allows for insights into biological processes on the sub-cellular level and thus
	provides valuable information for systems biology studies. In this paper we present
	two new	techniques for automatic segmentation of cell areas and included sub-cellular
	particles. A new cascaded and intensity-adaptive segmentation scheme
	based on coupled active contours is used to segment cell areas. Structures on
	the sub-cellular level, i.e. stress granules and processing bodies, are detected applying
	a scale-adaptive wavelet-based detection technique. Combining these results
	yields fully automated analyses of biological processes, and allows for new insights
	into interactions between different cellular structures and their distributions
	among different cells. We present an experimental evaluation based on ground-truth
	data that confirms the high-quality of our segmentation results regarding
	these aims and opens perspectives towards deeper insights into biological systems
	for other problems from systems biology.},
  doi = {10.1007/978-3-642-25382-9},
  keywords = {Segmentation, wavelets, a contrario, active contours, fluorescent
	microscope imaging, cells, granules},
  url = {http://www.springer.com/computer/image+processing/book/978-3-642-25381-2 }
}
@inproceedings{Moeller10_VISAPP,
  author = {Birgit M{\"o}ller and Oliver Gre{\ss} and Nadine St{\"o}hr and Stefan
	H{\"u}ttelmaier and Stefan Posch},
  title = {Adaptive Segmentation of cells and particles in fluorescent microscope
	images},
  booktitle = {Proc. of International Conference on Computer Vision Theory and Applications
	(VISAPP '10)},
  year = {2010},
  volume = {2},
  pages = {97-106},
  address = {Angers, France},
  month = {May},
  abstract = {Microscope imaging is an indispensable tool in modern systems biology.
	In combination with fully automatic image analysis it allows for
	valuable insights into biological processes on the sub-cellular level
	and fosters understanding of biological systems. In this paper we
	present two new techniques for automatic segmentation of cell areas
	and included sub-cellular particles. A new cascaded and intensity-adaptive
	segmentation scheme based on coupled active contours is used to segment
	cell areas. Structures on the sub-cellular level, i.e. stress granules
	and processing bodies, are detected applying a scale-adaptive wavelet-based
	detection technique. Combining these results allows for complementary
	analysis of biological processes. It yields new insights into interactions
	between different particles and distributions of particles among
	different cells. Our experimental evaluations based on ground-truth
	data prove the high-quality of our segmentation results regarding
	these aims and open perspectives towards deeper insights into biological
	systems on the sub-cellular level.}
}
@inproceedings{Moeller12_IJ,
  author = {B. M{\"o}ller and D. Misiak},
  title = {Snake Optimizer - Object Segmentation with Parametric Active Contours
	in ImageJ},
  booktitle = {Proc. of ImageJ User \& Developer Conference},
  year = {2012},
  pages = {215-217, 222},
  address = {Mondorf-les-Bains, Luxembourg},
  month = {October},
  abstract = {Parametric active contour models, commonly denoted as snakes, provide
	an integrated framework for transforming object segmentation tasks into 
        well-founded mathematical optimization problems. Over the years snakes
	have proven large flexibility in segmenting a great variety of different
	objects in lots of setups. Nevertheless, each new object segmentation problem 
        again raises the question if snakes are capable of solving the problem
	and if so, which combination of energies to apply. Here we present
	our ImageJ plugin 'SnakeOptimizer' which implements object segmentation 
        based on 2D parametric active contours.	It is well-suited to support users in
	answering the above questions during rapid-prototyping stages, as
	well as for being integrated into productive analysis workflows. 
        The functional core of the implementation can easily be extended with new energy models
	based on functionality provided by Alida.1 The ImageJ plugin features
	a handy GUI for interactive use, and the optimizer can also be run headless from 
        command line or on the programming level using its intuitive API.},
  comment = {ISBN 2-919941-18-6},
  keywords = {Image Segmentation, Active Contours, Snakes, ImageJ, Alida}
}
@inproceedings{Moeller08_ICPR,
  author = {Birgit M{\"o}ller and Thomas Pl{\"o}tz and Gernot Fink},
  title = {Calibration-free Camera Hand-Over for Fast and Reliable Person Tracking
	in Multi-Camera Setups},
  booktitle = {Proc. of Int. Conf. on Pattern Recognition (ICPR '08)},
  year = {2008},
  pages = {1-4},
  address = {Tampa, Florida, USA},
  month = {December},
  publisher = {IEEE},
  abstract = {Ensembles of multiple (active) cameras yield an important ingredient
	in modern tracking and surveillance applications. They overcome the
	limited fields-of-view of single cameras, however, require robust
	procedures for handing over tracking tasks from one camera to another.
	In this paper a calibration-free procedure is proposed that allows
	for fast and reliable camera hand-over in Ambient Intelligence (AmI)
	applications. The approach is based on online acquisition of scenario-specific
	target models and especially solves the problem of significant changes
	in object view during hand-over. Real-world results acquired in an
	AmI environment prove the effectiveness of our technique.},
  url = {http://figment.csee.usf.edu/~sfefilat/data/papers/TuAT9.19.pdf}
}
@inproceedings{Moeller02_DAGM,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {Analysis of Object Interactions in Dynamic Scenes},
  booktitle = {Pattern Recognition, Proc. of 24th DAGM Symposium},
  year = {2002},
  editor = {L. van Gool},
  series = {LNCS 2449},
  pages = {361-369},
  address = {Zurich, Switzerland},
  month = {September},
  publisher = {Springer},
  abstract = {One important source of information in scene understanding is given
	by actions performed either by human actors or robots. In this paper
	an approach to recognition and low-level interpretation of actions
	is presented. Since actions are characterized by specific motion
	patterns of moving objects, recognition is done by detecting such
	motion patterns as specific constellations of interactions between
	moving objects. First of all, motion detection and tracking algorithms
	are applied to extract correspondences between moving objects in
	consecutive images of a sequence. Subsequently these are represented
	with a graph data-structure for further analysis. To detect interactions
	of moving objects robustly a short history of motion of objects is
	traced using a finite-state automaton. Finally activities are segmented
	based on detected interactions. Since robust motion data are required
	consistency checks and corrections of the acquired motion data are
	performed in parallel.},
  isbn = {3-540-44209-X},
  numpages = {9},
  url = {http://www.springerlink.com/content/1fgrp9l90vjac9f1/fulltext.pdf}
}
@inproceedings{Moeller05_Koblenz,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {Visual Scene Memory Based on Multi-Mosaics},
  booktitle = {Mixed-reality as a challenge to image understanding and artificial
	intelligence},
  year = {2005},
  editor = {Dietrich Paulus and Detlev Droege},
  pages = {27-32},
  address = {Koblenz},
  organization = {Universit{\"a}t Koblenz-Landau, Institut f{\"u}r Informatik},
  abstract = {Visual data acquired with active cameras yields an important source
	of information for interactive systems. However, since image sequences
	usually comprise large data volumes and notable portions of redundant
	information analysis is often diffcult. Hence, data structures are
	required that allow for compact representation of image sequences.
	In this paper we introduce our concept of a visual scene memory.
	The memory is based on mosaic images enabling compact image sequence
	representation by fusing all sequence images into one single frame
	while eliminating redundancies. Since interactive systems put special
	demands on mosaicing techniques we developed a new mosaic concept
	called multi-mosaics well-suited to be used with interactive systems.
	The memory is focussed on adaquate representation of iconic data,
	however, not restricted to it. Rather higher-level data, particularly
	motion data as well as data suitable for active camera control are
	additionally included completing the visual scene representation.},
  isbn = {1860-4471}
}
@inproceedings{Moeller01_DAGM,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {Detection and Tracking of Moving Objects for Mosaic Image Generation},
  booktitle = {Pattern Recognition, Proc. of 23rd DAGM Symposium},
  year = {2001},
  editor = {B. Radig and S. Florczyk},
  series = {LNCS 2191},
  pages = {208-215},
  address = {Munich, Germany},
  month = {September},
  publisher = {Springer},
  abstract = {Mosaic images provide an efficient representation of image sequences
	and simplify scene exploration and analysis. However, the application
	of conventional methods to generate mosaics of scenes with moving
	objects causes integration errors and a loss of dynamic information.
	In this paper a method to compute mosaics of dynamic scenes is presented
	addressing the above mentioned problems. Moving pixels are detected
	in the images and not integrated in the mosaic yielding a consistent
	representation of the static scene background. Furthermore, dynamic
	object information is extracted by tracking moving regions. To account
	for unavoidable variances in region segmentation topologically neighboring
	regions are grouped into sets before tracking. The regions' and objects'
	motion characteristics are described by trajectories. Along with
	the background mosaic they provide a complete representation of the
	underlying scene which is idealy suited for further analysis.},
  isbn = {3-540-42596-9},
  numpages = {8},
  url = {http://dl.acm.org/citation.cfm?id=756114}
}
@inproceedings{Moeller12_ISBI,
  author = {B. M{\"o}ller and S. Posch},
  title = {Comparing Active Contours for the Segmentation of Biomedical Images},
  booktitle = {Proc. of IEEE International Symposium on Biomedical Imaging (ISBI)},
  year = {2012},
  pages = {736-739},
  address = {Barcelona, Spain},
  month = {May},
  note = {IEEE Catalog No.: CFP12BIS-CDR, ISBN: 978-1-4577-1856-4},
  abstract = {Application of active contours for image segmentation raises the question
	of contour representation, i.e. whether to use snakes or level sets.
	The representation directly affects is- sues like topology-preservation
	and energy optimization. In this paper we aim to contribute to the
	understanding of spe- cific characteristics of contour representations
	with a detailed comparison of snakes vs. non-PDE level sets. Based
	on the same energy functional and applied to different kinds of real-
	world data our experiments show minor differences in seg- mentation
	quality, but outline important distinctions regarding implementation,
	parameter settings and computational effort.},
  keywords = {Snakes, non-PDE level sets, comparison},
  url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=6235653&contentType=Conference+Publications&sortType%3Dasc_p_Sequence%26filter%3DAND%28p_IS_Number%3A6235468%29%26pageNumber%3D8}
}
@inproceedings{Moeller11_MIAAB,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {{MiCA} - Easy Cell Image Analysis with Normalized Snakes},
  booktitle = {International Workshop on Microscopic Image Analysis with Applications
	in Biology},
  year = {2011},
  address = {Heidelberg, Germany},
  month = {September},
  abstract = {Quantitative analysis of microscopy cell images requires accurate
	detection of cell boundaries, nuclei and sub-cellular structures.
	Accordingly, tools for integrated cell image analysis are required
	which not only provide a variety of different segmentation and detection
	algorithms, but at the same time support easy usage also by life
	scientists. In this paper we present our integrated cell analysis
	tool MiCA offering different segmentation techniques, e.g., based
	on wavelets or snakes. Iterative optimization of snake energies depends
	on a variety of parameters that require thorough adjustment for optimal
	results. To facilitate easy use of these techniques MiCA provides
	a new energy normalization scheme for snakes allowing for intuitive
	interpretation of energy parameters and, thus, simplified cell image
	analysis. The high quality of the result data of MiCA is proven on
	two sample data sets by qualitative assessments and ground-truth
	comparisons.},
  city = {Heidelberg},
  pdf = {http://www.miaab.org/miaab-2011-heidelberg-papers/miaab-2011-h-moeller.pdf}
}
@article{Moeller09_Elec,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {Robust Features for 2-D Electrophoresis Gel Image Registration},
  journal = {Electrophoresis},
  year = {2009},
  volume = {30},
  pages = {4137-4148},
  abstract = {Proteomics is a rapidly growing field of modern biology. Since quantitative
	data of proteins involved in dynamic processes of living organisms
	are essential for understanding the basics of life, techniques like
	2-DE and related procedures for automatic data interpretation are
	at the heart of this research field. They are strongly required to
	enable analysis and interpretation of the emerging amount of available
	data. Analyzing and interpreting gel image data usually requires
	the comparison of gels from different experiments and, thus, a prior
	registration of gels. This can be accomplished using featureless,
	feature-based or hybrid registration approaches combining both techniques.
	Recently, the latter ones have shown high performance, and it is
	undoubtful that in general robust and reliable features are an essential
	ingredient and valuable source of information for high-quality image
	registration. In this paper we provide a thorough overview and elaborate
	analysis of the capabilities of available feature detectors for gel
	image registration. Particularly, a detailed and extensive comparative
	study is presented where common spot-specific detectors are included
	as well as image-content independent detectors that were not applied
	to the task of gel image registration until now. The study incorporates
	tests on several thousand synthetically deformed images from different
	experimental conditions. As a result it provides valuable quantitative
	data allowing for direct objective comparisons of various detectors,
	and is well suited to guide the design of new registration algorithms.},
  doi = {10.1002/elps.200900293},
  keywords = {2-DE; Comparative study; Feature detectors; Image registration; Keypoints},
  url = {http://onlinelibrary.wiley.com/doi/10.1002/elps.200900293/full}
}
@article{Moeller08_PRIA,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {An Integrated Analysis Concept for Errors in Image Registration},
  journal = {Int. Journal on Pattern Recognition and Image Analysis (PRIA)},
  year = {2008},
  volume = {18},
  pages = {201-206},
  number = {2},
  abstract = {Image registration is an important ingredient in a wide variety of
	computer vision applications. Over the years countless algorithms
	emerged that allow for robust registration of image sequences. Unfortunately,
	high quality results still cannot be guaranteed in any case. Especially
	in interactive online systems that strongly rely on results of unsupervised
	registration algorithms, techniques for automatic quality analysis
	and failure compensation are indispensable. In this paper we present
	a new concept for an integrated and fully automatic detection and
	analysis of errors in registration. Based on a new metric for registration
	quality assessment, image differences are robustly detected. In addition,
	a hierarchical analysis scheme is proposed that allows distinguishing
	between various underlying error sources, all having different impacts
	on a registration result and requesting for individual compensation
	strategies.},
  doi = {10.1134/S105466180802003X},
  publisher = {Springer},
  pdf = {http://www.springerlink.com/content/94j30064x573x783/fulltext.pdf}
}
@inproceedings{Moeller07_BMVC,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {Identifying Lens Distortions in Image Registration by Learning from
	Examples},
  booktitle = {Proc. of British Machine Vision Conference (BMVC '07)},
  year = {2007},
  pages = {I:152-161},
  address = {University of Warwick, Coventry, UK},
  month = {September},
  abstract = {Automatic quality assessment of image registration results is an important
	issue in image processing. Many applications strongly depend on accurate
	registration results, sometimes even requiring automatic self-recovery
	from registration failures. In doing so it is not sufficient just
	to detect registration errors. Also a distinction between different
	error sources is necessary, as each source has an individual impact
	on the final registration result and requires specific compensation
	strategies. We present a new approach to automatically identify lens
	distortions in image pairs, known to have a significant impact on
	registration. The key idea is to analyse registration residuals and
	to learn a model of spatial residual distributions typical for distorted
	images. Our approach relies on a new metric for registration quality
	assessment and implements a regression scheme based on SVMs for predicting
	distortions in unknown data. The potential of the approach is demonstrated
	by experimental results on synthetic as well as real image data.},
  pdf = {http://www.dcs.warwick.ac.uk/bmvc2007/proceedings/CD-ROM/papers/paper-123.pdf }
}
@inproceedings{Moeller07_CCMVS,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {Automatic Analysis of Lens Distortions in Image Registration},
  booktitle = {Proc. of Int. Conf. on Computer Vision Systems (ICVS '07), Workshop
	on Camera Calibration Methods for Computer Vision Systems (CCMVS
	'07)},
  year = {2007},
  address = {Bielefeld, Germany},
  month = {March},
  abstract = {Geometric image registration by estimating homographies is an important
	processing step in a wide variety of computer vision applications.
	The 2D registration of two images does not require an explicit reconstruction
	of intrinsic or extrinsic camera parameters. However, correcting
	images for non-linear lens distortions is highly recommended. Unfortunately,
	standard calibration techniques are sometimes difficult to apply
	and reliable estimations of lens distortions can only rarely be obtained.
	In this paper we present a new technique for automatically detecting
	and categorising lens distortions in pairs of images by analysing
	registration results. The approach is based on a new metric for registration
	quality assessment and facilitates a PCA-based statistical model
	for classifying distortion effects. In doing so the overall importance
	for lens calibration and image corrections can be checked, and a
	measure for the efficiency of accordant correction steps is given.},
  doi = {10.2390/biecoll-icvs2007-174},
  keywords = {Camera Calibration, Lens Distortions, Image Registration, Automatic
	Assessment, Statistical Classification},
  pdf = {http://www.icvs2007.org/ccmvs/CCMVS2007-174.pdf },
  url = {http://biecoll.ub.uni-bielefeld.de//frontdoor.php?source_opus=98&la=en}
}
@inproceedings{Moeller07_OGRW,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {An Integrated Analysis Concept for Errors in Image Registration},
  booktitle = {Proc. of 7th Open German/Russian Workshop on Pattern Recognition
	and Image Understanding (OGRW '07)},
  year = {2007},
  address = {Ettlingen, Germany},
  month = {August},
  abstract = {Image registration is an important ingredient in a wide variety of
	computer vision applications. Over the years countless algorithms
	emerged that allow for robust registration of image sequences. Unfortunately,
	high quality results still cannot be guaranteed in any case. Especially
	in interactive online systems that strongly rely on results of unsupervised
	registration algorithms, techniques for automatic quality analysis
	and failure compensation are indispensable. In this paper we present
	a new concept for an integrated and fully automatic detection and
	analysis of errors in registration. Based on a new metric for registration
	quality assessment, image differences are robustly detected. In addition,
	a hierarchical analysis scheme is proposed that allows to distinguish
	between various underlying error sources, all having different impacts
	on a registration result and requesting for individual compensation
	strategies.}
}
@techreport{Moeller07_TR,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {An Iconic Scene Memory Approach for Mobile Robots Interacting with
	Humans},
  institution = {Institute of Computer Science, Martin-Luther-University Halle-Wittenberg,
	Germany},
  year = {2007},
  type = {Technical Report},
  number = {2007-03},
  month = {December},
  abstract = {Robots that support humans in their private homes by carrying out
	tasks of everyday life require sophisticated skills. Among others
	they have to provide multi-modal communication facilities, and also
	generic recognition and learning capabilities are indispensable.
	However, several of these skills, e.g., the recognition of objects,
	cannot be seen in isolation. Rather cognitive motivated approaches
	are on demand that integrate aspects of perception, reasoning and
	learning. Since all of these processes strongly rely on memorising
	and recalling data a visual memory component yields a fundamental
	building block of cognitive motivated system architectures.
	
	Such a memory usually subsumes different levels of abstraction ranging
	from low-level iconic to high-level categorial data and will often
	be organised hierarchically. Within this paper we propose an extended
	iconic scene representation for low level visual data, the SMARD
	memory module.
	
	It is particularly designed to meet the requirements of interactive
	and mobile robotic systems. These systems significantly benefit from
	such a memory component, however, at the same time they enforce strict
	constraints on its architecture, e.g., regarding flow of data and
	control or resource management strategies. Our approach is based
	on mosaic images that are computed following an incremental strategy.
	Due to polytopial coordinate frames they support easy data access
	and a direct analysis. The practical relevance of our approach is
	outlined by two example applications that illustrate its benefits
	with regard to intuitive and efficient human-robot interaction.},
  pdf = {http://wcms-neu1.urz.uni-halle.de/download.php?down=5355&elem=1555433}
}
@inproceedings{Moeller06_VISAPP,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {A Space- and Time-Efficient Mosaic-Based Iconic Memory for Interactive
	Systems},
  booktitle = {Proc. of International Conference on Computer Vision Theory and Applications
	(VISAPP '06)},
  year = {2006},
  pages = {413-421},
  address = {Set{\'u}bal, Portugal},
  month = {February},
  note = {to appear.},
  abstract = {One basic capability of interactive and mobile systems to cope with
	unknown situations and environments is active, sequence-based visual
	scene analysis. Image sequences provide static as well as dynamic
	and also 2D as well as 3D information about a certain scene. However,
	at the same time they require efficient mechanisms to handle their
	large data volumes. In this paper we introduce a new concept of a
	visual scene memory for interactive mobile systems that supports
	these systems with a space- and time-efficient data structure for
	representing iconic information. The memory is based on a new kind
	of mosaic images called multi-mosaics and allows to efficiently store
	and process sequences of stationary rotating and zooming cameras.
	Its main key features are polytopial reference coordinate frames
	and an online data processing strategy. The polytopes provide euclidean
	coordinates and thus allow the application of standard image analysis
	algorithms directly to the data yielding easy access and analysis,
	while online data processing preserves system interactivity. Additionally,
	mechanisms are included to properly handle multi-resolution data
	and to deal with dynamic scenes. The concept has been implemented
	in terms of an integrated system that can easily be included as an
	additional module in the architecture of interactive and mobile systems.
	As one prototypical example for possible fields of application the
	integration of the memory into the architecture of an interactive
	multi-modal robot is discussed emphasizing the practical relevancy
	of the new concept.}
}
@inproceedings{Moeller05_Mirage,
  author = {Birgit M{\"o}ller and Stefan Posch},
  title = {A Mosaic-based Visual Memory with Applications to\\Active Scene Exploration},
  booktitle = {Proc. of Mirage, Computer Vision / Computer Graphics Collaboration
	Techniques and Applications},
  year = {2005},
  pages = {117-125},
  address = {INRIA Rocquencourt, France},
  month = {March},
  abstract = {Processing visual data is an important ability of interactive systems
	to act in dynamically changing environments. Looking at the human
	visual and cognitive system this requires efficient mechanisms for
	data processing and storage as well as intelligent strategies for
	data acquisition. In this paper we present a visual memory supporting
	efficient representation of image sequences of active cameras in
	an online fashion. The memory is based on mosaic images extending
	the field of view of a camera in space and time. As one prototypical
	field of application for the memory active scene exploration is discussed.
	The temporally and spatially integrated data of the memory combined
	with additional feature maps serves as an ideal starting point for
	the selection of focus points. Hence the memory demonstrates the
	combination of efficient acquisition and storage of visual data and
	helps to provide interactive systems with high flexibility to operate
	in dynamically changing environments.}
}
@inproceedings{Moeller05_IROS,
  author = {B. M{\"o}ller and S. Posch and A. Haasch and J. Fritsch and G. Sagerer},
  title = {Interactive Object Learning for Robot Companions using Mosaic Images},
  booktitle = {Proc. IEEE/RSJ Int. Conf. on Intelligent Robots and Systems},
  year = {2005},
  pages = {2650 - 2655},
  address = {Edmonton, Alberta, Canada},
  month = {August},
  abstract = {Natural human-robot interaction (HRI) is a key feature of mobile robot
	companions collaborating with humans. To achieve natural HRI, multiple
	communication modalities like vision, speech, and gestures have to
	be utilized. Besides, capabilities to emulate cognitive processes,
	e.g., object learning and object recognition, are essential. In this
	work we present a new approach to interactive object learning enabling
	multi-view object representation. To overcome a robot's limitation
	of having only one view point, we make use of an iconic memory consisting
	of previously acquired images. As the relevant scene area is unknown
	during construction of the iconic memory, a representation in the
	form of mosaic images is applied. The relevant image patches describing
	an object referenced by the user are selected through an object attention
	mechanism. The resulting multi-view object representations improve
	the flexibility of our interactive approach for object learning.},
  url = {http://ieeexplore.ieee.org/iel5/10375/32977/01545009.pdf?isnumber=&arnumber=1545009}
}
@inproceedings{Moeller10_ICPR,
  author = {Birgit M{\"o}ller and Nadine St{\"o}hr and Stefan H{\"u}ttelmaier
	and Stefan Posch},
  title = {Cascaded Segmentation of Grained Cell Tissue with Active Contour
	Models},
  booktitle = {Proceedings International Conference on Pattern Recognition},
  year = {2010},
  pages = {1481-1484},
  address = {Istanbul, Turkey},
  month = {August},
  publisher = {IEEE},
  abstract = {Cell tissue in microscope images is often grained and its intensities
	do not well agree with Gaussian distribution assumptions widely used
	in many segmentation approaches. We present a new cascaded segmentation
	scheme for inhomogeneous cell tissue based on active contour models.
	Cell regions are iteratively expanded from initial nuclei regions
	applying a data-dependent number of optimization levels. Experimental
	results on a set of microscope images from a human hepatoma cell
	line prove high quality of the results with regard to the cell segmentation
	task and biomedical investigations.},
  url = {http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=5597237}
}
@inproceedings{Moeller03_DAGM,
  author = {Birgit M{\"o}ller and Denis Williams and Stefan Posch},
  title = {Robust Image Sequence Mosaicing},
  booktitle = {Pattern Recognition, Proc. of 25th DAGM Symposium},
  year = {2003},
  editor = {B. Michaelis and G. Krell},
  series = {LNCS 2781},
  pages = {386-393},
  address = {Magdeburg, Germany},
  month = {September},
  publisher = {Springer},
  abstract = {Mosaicing is a technique to efficiently condense the static information
	of an image sequence within one extended mosaic image. The core of
	mosaicing is to estimate a global transformation between images due
	to the global camera motion. This is usually accomplished by either
	matching segmented image features or exploiting all iconic image
	data directly within a featureless approach. In this paper we propose
	to combine aspects from both techniques where we abandon to segment
	features, however select pixels to be used for parameter estimation
	based on structural image data and information about independently
	moving scene parts. While this results in a speed up of the estimation
	process the main focus is to improve robustness with respect to ambiguities
	arising from homogeneous image regions and to motion in the scene.},
  url = {http://www.springerlink.com/content/81w82twx323pvtm0/fulltext.pdf}
}
@article{Moeller04_PRIA,
  author = {Birgit M{\"o}ller and Denis Williams and Stefan Posch},
  title = {Towards a Mosaic-based Visual Representation of Large Scenes},
  journal = {Int. Journal on Pattern Recognition and Image Analysis, Spec. Issue},
  year = {2004},
  volume = {14(2)},
  pages = {262-266},
  abstract = {Interactive systems using active cameras produce a large amount of
	image data to be processed. The task of a visual memory is to represent
	this data in an efficient way and thus assisting subsequent image
	analysis algorithms. In this paper we extent our mosaic based approach
	to large scenes where distortions occur if the camera rotation covers
	a wide angle. This problem can be solved by using a spherical mosaic
	surface. However, since most vision algorithms are created for planar
	images we propose to tile the sphere with planar patches resulting
	in a mosaic polytope we call multi-mosaic. A more spacious scene
	can be represented by a number of such multi-mosaics taken from different
	spatial positions. If a mobile robot is used for image acquisition
	the path in between can additionally be represented by manifold mosaics
	to connect the positions.}
}
@inproceedings{Moeller03_OGRW,
  author = {Birgit M{\"o}ller and Denis Williams and Stefan Posch},
  title = {Towards a Mosaic-based Visual Representation of Large Scenes},
  booktitle = {Proc. of 6th Open German-Russian Workshop (IAPR)},
  year = {2003},
  pages = {108-111},
  address = {Katun Village, Altai Region, Russian Federation},
  month = {25.-30. August},
  abstract = {Interactive systems using active cameras produce a big amount of image
	data to be processed. The task of a visual memory is to represent
	this data in an efficient way and thus assisting subsequent image
	analysis algorithms. In this paper we extent our mosaic based approach
	to large scenes where distortions occure if the camera rotation covers
	a wide angle. This problem can be solved by using a spherical mosaic
	surface. However, since most vision algorithms are created for planar
	images we propose to tile the sphere with planar patches resulting
	in a mosaic polytope we call multi-mosaic. A more spacious scene
	can be represented by a number of such multi-mosaics taken from different
	spatial positions. If a mobile robot is used for image acquisition
	the path in between can additionally be represented (by manifold
	mosaics) to connect the positions.}
}
@inproceedings{Posch12_IJ,
  author = {S. Posch and B. M{\"o}ller},
  title = {Automatic Generation of Processing Histories using Alida},
  booktitle = {Proc. of ImageJ User \& Developer Conference},
  year = {2012},
  pages = {218-221},
  address = {Mondorf-les-Bains, Luxembourg},
  month = {October},
  abstract = {Analysis of data is subject of many fields of applications. Besides
	the results per se, the documentation of analysis processes is important
        for later verification, reconstruction,	or publication. As manual documentation
	is tedious and error prone the Java library Alida provides fully automatic
	extraction of processing histories.
	As applications we present our own image processing toolbox MiToBo
	based on ImageJ and demonstrate the integration of Alida into ImageJ 2.0.},
  comment = {ISBN 2-919941-18-6},
  keywords = {Processing History, Process Documentation, Processing Graph, XML,
	Alida, ImageJ}
}
@inproceedings{Posch12_ISBI_WS,
  author = {S. Posch and B. M{\"o}ller},
  title = {Alida - Automatic Generation of User Interfaces for Data Analysis
	Algorithms},
  booktitle = {Proc. of IEEE International Symposium on Biomedical Imaging (ISBI),
	Bioimage Analysis Workshop},
  year = {2012},
  address = {Barcelona, Spain},
  month = {May},
  note = {Poster presentation},
  abstract = {Analysis of biomedical data may be interpreted as a flow of objects
	through an analysis pipeline. The Java framework Alida (http://www.informatik.uni-halle.de/alida)
	defines the concept of operators as the single places of these manipulations.
	Typically, operators may be invoked sequentially or in parallel,
	and often also nested. Besides invocation on the programming level
	their functionality should also be available directly to users, including
	developers of algorithms and non-experts. This calls for graphical
	as well as command line interfaces. Eliminating the need to explicitly
	code these interfaces, Alida features fully automated generation
	of graphical and command line user interfaces for each operator implemented
	in the Alida framework.
	
	 The basis is a formalism for an operator to define all input and
	output data objects and parameters to control processing. Automatic
	generation of interfaces is based on the model view presenter design
	pattern to achieve maximal independence between the operators, interfaces,
	and I/O of data objects. For implementation Java's annotation mechanism
	is used. The programmer is only required to properly annotate classes
	and member variables. Out of the box this facilitates I/O for a wide
	variety of Java objects including primitive data types, enumerations,
	arrays, and collections. In a generic way Alida handles also operators
	as parameters of other operators and inheritance. Only specialized
	classes like images require additional data providers to be implemented.
	
	 While Alida is devised for data processing in general, it is used
	in our image analysis toolbox MiToBo (http://www.informatik.uni-halle.de/mitobo)
	for biomedical image analysis which is based on ImageJ and compatible
	to it.}
}
@inproceedings{Moeller03_CISST,
  author = {Denis Williams and Birgit M{\"o}ller and Stefan Posch},
  title = {Integrated System for a Visual Memory Based on Mosaics},
  booktitle = {Proceedings of International Conference on Imaging Science, Systems,
	and Technology (CISST'03)},
  year = {2003},
  editor = {H.R. Arabnia and Youngsong Mun},
  pages = {II: 633-639},
  address = {Monte Carlo Resort, Las Vegas, Nevada, USA},
  month = {23.-26. June},
  publisher = {CSREA Press},
  abstract = {Exploring a scene with an active camera yields an image sequence containing
	implicit information of the environment, but also a considerable
	amount of redundancies. In this paper the system AViSMo is described
	to explicitly represent the information about the scene in a visual
	memory. It is based on the construction of a mosaic image containing
	non-redundantly iconic data of static scene parts. This mosaic is
	augmented with trajectories of moving objects, activities detected
	from image data in a bottom-up fashion, and external high-level data.
	AViSMo is a highly modular and extendable system, capable of communicating
	with external components using a variety of transport mechanisms.
	As an example of such an external component it comprises a GUI to
	control and visualize the mosaicing process. Thus, it is ideally
	suited to supply interactive systems with a visual scene memory.}
}

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