@article {48647, title = {The candidate multi-cut for cell segmentation.}, journal = {2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018)}, year = {2017}, month = {2017 Jul 04}, abstract = {

Two successful approaches for the segmentation of biomedical images are (1) the selection of segment candidates from a merge-tree, and (2) the clustering of small superpixels by solving a Multi-Cut problem. In this paper, we introduce a model that unifies both approaches. Our model, the Candidate Multi-Cut (CMC), allows joint selection and clustering of segment candidates from a merge-tree. This way, we overcome the respective limitations of the individual methods: (1) the space of possible segmentations is not constrained to candidates of a merge-tree, and (2) the decision for clustering can be made on candidates larger than superpixels, using features over larger contexts. We solve the optimization problem of selecting and clustering of candidates using an integer linear program. On datasets of 2D light microscopy of cell populations and 3D electron microscopy of neurons, we show that our method generalizes well and generates more accurate segmentations than merge-tree or Multi-Cut methods alone.

}, doi = {10.1109/ISBI.2018.8363658}, author = {Funke, Jan and Zhang, Chong and Pietzsch, Tobias and Gonzalez Ballester, Miguel A and Saalfeld, Stephan} } @article {48278, title = {Multi-view light-sheet imaging and tracking with the MaMuT software reveals the cell lineage of a direct developing arthropod limb.}, journal = {eLife}, volume = {7}, year = {2017}, month = {2018 Mar 29}, pages = {e34410}, abstract = {

During development, coordinated cell behaviors orchestrate tissue and organ morphogenesis. Detailed descriptions of cell lineages and behaviors provide a powerful framework to elucidate the mechanisms of morphogenesis. To study the cellular basis of limb development, we imaged transgenic fluorescently-labeled embryos from the crustacean Parhyale hawaiensis with multi-view light-sheet microscopy at high spatiotemporal resolution over several days of embryogenesis. The cell lineage of outgrowing thoracic limbs was reconstructed at single-cell resolution with new software called Massive Multi-view Tracker (MaMuT). In silico clonal analyses suggested that the early limb primordium becomes subdivided into anterior-posterior and dorsal-ventral compartments whose boundaries intersect at the distal tip of the growing limb. Limb-bud formation is associated with spatial modulation of cell proliferation, while limb elongation is also driven by preferential orientation of cell divisions along the proximal-distal growth axis. Cellular reconstructions were predictive of the expression patterns of limb development genes including the BMP morphogen Decapentaplegic.

}, doi = {10.7554/eLife.34410}, author = {Wolff, Carsten and Tinevez, Jean-Yves and Pietzsch, Tobias and Stamataki, Evangelia and Harich, Benjamin and Guignard, Leo and Preibisch, Stephan and Shorte, Spencer and Keller, Philipp J and Tomancak, Pavel and Pavlopoulos, Anastasios} } @article {46817, title = {BigDataViewer: visualization and processing for large image data sets.}, journal = {Nature Methods}, volume = {12}, year = {2015}, month = {2015 May 28}, pages = {481-3}, issn = {1548-7105}, doi = {10.1038/nmeth.3392}, author = {Pietzsch, Tobias and Saalfeld, Stephan and Preibisch, Stephan and Tomancak, Pavel} } @article {45049, title = {Bioimage informatics in the context of Drosophila research.}, journal = {Methods}, volume = {68}, year = {2014}, month = {2014 Jun 15}, pages = {60-73}, abstract = {

Modern biological research relies heavily on microscopic imaging. The advanced genetic toolkit of Drosophila makes it possible to label molecular and cellular components with unprecedented level of specificity necessitating the application of the most sophisticated imaging technologies. Imaging in Drosophila spans all scales from single molecules to the entire populations of adult organisms, from electron microscopy to live imaging of developmental processes. As the imaging approaches become more complex and ambitious, there is an increasing need for quantitative, computer-mediated image processing and analysis to make sense of the imagery. Bioimage Informatics is an emerging research field that covers all aspects of biological image analysis from data handling, through processing, to quantitative measurements, analysis and data presentation. Some of the most advanced, large scale projects, combining cutting edge imaging with complex bioimage informatics pipelines, are realized in the Drosophila research community. In this review, we discuss the current research in biological image analysis specifically relevant to the type of systems level image datasets that are uniquely available for the Drosophila model system. We focus on how state-of-the-art computer vision algorithms are impacting the ability of Drosophila researchers to analyze biological systems in space and time. We pay particular attention to how these algorithmic advances from computer science are made usable to practicing biologists through open source platforms and how biologists can themselves participate in their further development.

}, issn = {1095-9130}, doi = {10.1016/j.ymeth.2014.04.004}, author = {Jug, Florian and Pietzsch, Tobias and Preibisch, Stephan and Tomancak, Pavel} } @proceedings {46790, title = {Advanced Programming with ImgLib2}, year = {2012}, month = {2012 Oct 24}, address = {Mondorf-les-Bains, Luxembourg}, author = {Pietzsch, Tobias and Preibisch, Stephan and Tomancak, Pavel and Saalfeld, Stephan} } @article {5634, title = {Fiji: an open-source platform for biological-image analysis.}, journal = {Nature Methods}, volume = {9}, year = {2012}, month = {2012 Jul}, pages = {676-82}, abstract = {

Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.

}, keywords = {Algorithms, Animals, Brain, Computational Biology, Computer-Assisted, Drosophila melanogaster, Image Enhancement, Image Processing, Imaging, Information Dissemination, Software, Software Design, Three-Dimensional}, issn = {1548-7105}, doi = {10.1038/nmeth.2019}, author = {Schindelin, Johannes and Arganda-Carreras, Ignacio and Frise, Erwin and Kaynig, Verena and Longair, Mark and Pietzsch, Tobias and Preibisch, Stephan and Rueden, Curtis and Saalfeld, Stephan and Schmid, Benjamin and Tinevez, Jean-Yves and White, Daniel James and Hartenstein, Volker and Eliceiri, Kevin and Tomancak, Pavel and Cardona, Albert} } @article {46160, title = {ImgLib2--generic image processing in Java.}, journal = {Bioinformatics}, volume = {28}, year = {2012}, month = {2012 Nov 15}, pages = {3009-11}, abstract = {

SUMMARY: ImgLib2 is an open-source Java library for n-dimensional data representation and manipulation with focus on image processing. It aims at minimizing code duplication by cleanly separating pixel-algebra, data access and data representation in memory. Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation. ImgLib2 illustrates that an elegant high-level programming interface can be achieved without sacrificing performance. It provides efficient implementations of common data types, storage layouts and algorithms. It is the data model underlying ImageJ2, the KNIME Image Processing toolbox and an increasing number of Fiji-Plugins.

AVAILABILITY: ImgLib2 is licensed under BSD. Documentation and source code are available at http://imglib2.net and in a public repository at https://github.com/imagej/imglib.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics Online.

CONTACT: saalfeld@mpi-cbg.de

}, keywords = {Algorithms, Image Processing, Computer-Assisted, Programming Languages, Software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/bts543}, author = {Pietzsch, Tobias and Preibisch, Stephan and Tomancak, Pavel and Saalfeld, Stephan} } @proceedings {46789, title = {ImgLib2{\textemdash}Generic Image Processing in Java}, year = {2012}, month = {2012 Oct 24}, address = {Mondorf-les-Bains, Luxembourg}, author = {Saalfeld, Stephan and Pietzsch, Tobias and Tomancak, Pavel and Preibisch, Stephan} } @proceedings {46791, title = {Introduction to ImgLib2}, year = {2012}, month = {2012 Oct 24}, address = {Mondorf-les-Bains, Luxembourg}, author = {Preibisch, Stephan and Pietzsch, Tobias and Myers, Eugene and Tomancak, Pavel and Saalfeld, Stephan} }