@article {69457, title = {Deep-tissue transcriptomics and subcellular imaging at high spatial resolution}, journal = {Science}, year = {2025}, month = {2025 Feb 20}, abstract = {

Limited color channels in fluorescence microscopy have long constrained spatial analysis in biological specimens. Here, we introduce cycle Hybridization Chain Reaction (HCR), a method that integrates multicycle DNA barcoding with HCR to overcome this limitation. cycleHCR enables highly multiplexed imaging of RNA and proteins using a unified barcode system. Whole-embryo transcriptomics imaging achieved precise three-dimensional gene expression and cell fate mapping across a specimen depth of ~310 μm. When combined with expansion microscopy, cycleHCR revealed an intricate network of 10 subcellular structures in mouse embryonic fibroblasts. In mouse hippocampal slices, multiplex RNA and protein imaging uncovered complex gene expression gradients and cell-type-specific nuclear structural variations. cycleHCR provides a quantitative framework for elucidating spatial regulation in deep tissue contexts for research and potentially diagnostic applications.

bioRxiv preprint:\ 10.1101/2024.05.17.594641

}, doi = { 10.1126/science.adq2084}, url = {https://www.science.org/doi/10.1126/science.adq2084}, author = {Gandin, Valentina and Kim, Jun and Yang, Liang-Zhong and Lian, Yumin and Kawase, Takashi and Hu, Amy and Rokicki, Konrad and Fleishman, Greg and Tillberg, Paul and Aguilera Castrejon, Alejandro and Stringer, Carsen and Preibisch, Stephan and Liu, Zhe J.} } @article {69712, title = {Scalable image-based visualization and alignment of spatial transcriptomics datasets}, journal = {Cell Syst}, year = {2025}, month = {2025 Apr 17}, abstract = {

We present the "spatial transcriptomics imaging framework" (STIM), an imaging-based computational framework focused on visualizing and aligning high-throughput spatial sequencing datasets. STIM is built on the powerful, scalable ImgLib2 and BigDataViewer (BDV) image data frameworks and thus enables novel development or transfer of existing computer vision techniques to the sequencing domain characterized by datasets with irregular measurement-spacing and arbitrary spatial resolution, such as spatial transcriptomics data generated by multiplexed targeted hybridization or spatial sequencing technologies. We illustrate STIM{\textquoteright}s capabilities by representing, interactively visualizing, 3D rendering, automatically registering, and segmenting publicly available spatial sequencing data from 13 serial sections of mouse brain tissue and from 19 sections of a human metastatic lymph node. We demonstrate that the simplest alignment mode of STIM achieves human-level accuracy.

Preprint:\ www.biorxiv.org/content/early/2024/10/07/2021.12.07.471629

}, doi = {10.1016/j.cels.2025.101264}, url = {https://doi.org/10.1016/j.cels.2025.101264}, author = {Preibisch, Stephan and Innerberger, Michael and Le{\'o}n-Peri{\~n}{\'a}n, Daniel and Karaiskos, Nikos and Rajewsky, Nikolaus} } @article {69455, title = {Analysis of developmental gene expression using smFISH and in silico staging of C. elegans embryos}, journal = {bioRxiv}, year = {2024}, month = {2024 May 16}, abstract = {

Regulation of transcription during embryogenesis is key to development and differentiation. To study transcript expression throughout Caenorhabditis elegans embryogenesis at single-molecule resolution, we developed a high-throughput single-molecule fluorescence in situ hybridization (smFISH) method that relies on computational methods to developmentally stage embryos and quantify individual mRNA molecules in single embryos. We applied our system to sdc-2, a zygotically transcribed gene essential for hermaphrodite development and dosage compensation. We found that sdc-2 is rapidly activated during early embryogenesis by increasing both the number of mRNAs produced per transcription site and the frequency of sites engaged in transcription. Knockdown of sdc-2 and dpy-27, a subunit of the dosage compensation complex (DCC), increased the number of active transcription sites for the X chromosomal gene dpy-23 but not the autosomal gene mdh-1, suggesting that the DCC reduces the frequency of dpy-23 transcription. The temporal resolution from in silico staging of embryos showed that the deletion of a single DCC recruitment element near the dpy-23 gene causes higher dpy-23 mRNA expression after the start of dosage compensation, which could not be resolved using mRNAseq from mixed-stage embryos. In summary, we have established a computational approach to quantify temporal regulation of transcription throughout C. elegans embryogenesis and demonstrated its potential to provide new insights into developmental gene regulation.

}, doi = {10.1101/2024.05.15.594414}, url = {https://www.biorxiv.org/content/early/2024/05/16/2024.05.15.594414}, author = {Breimann, Laura and Bahry, Ella and Zouinkhi, Marwan and Kolyvanov, Klim and Street, Lena Annika and Preibisch, Stephan and Ercan, Sevin{\c c}} } @article {69713, title = {Analysis of developmental gene expression using smFISH and in silico staging of C. elegans embryos}, journal = {bioRxiv}, year = {2024}, month = {05/2024}, abstract = {

Regulation of transcription during embryogenesis is key to development and differentiation. To study transcript expression throughout Caenorhabditis elegans embryogenesis at single-molecule resolution, we developed a high-throughput single-molecule fluorescence in situ hybridization (smFISH) method that relies on computational methods to developmentally stage embryos and quantify individual mRNA molecules in single embryos. We applied our system to sdc-2, a zygotically transcribed gene essential for hermaphrodite development and dosage compensation. We found that sdc-2 is rapidly activated during early embryogenesis by increasing both the number of mRNAs produced per transcription site and the frequency of sites engaged in transcription. Knockdown of sdc-2 and dpy-27, a subunit of the dosage compensation complex (DCC), increased the number of active transcription sites for the X chromosomal gene dpy-23 but not the autosomal gene mdh-1, suggesting that the DCC reduces the frequency of dpy-23 transcription. The temporal resolution from in silico staging of embryos showed that the deletion of a single DCC recruitment element near the dpy-23 gene causes higher dpy-23 mRNA expression after the start of dosage compensation, which could not be resolved using mRNAseq from mixed-stage embryos. In summary, we have established a computational approach to quantify temporal regulation of transcription throughout C. elegans embryogenesis and demonstrated its potential to provide new insights into developmental gene regulation.Competing Interest StatementThe authors have declared no competing interest.

}, doi = {10.1101/2024.05.15.594414}, url = {https://www.biorxiv.org/content/early/2024/05/16/2024.05.15.594414}, author = {Breimann, Laura and Bahry, Ella and Zouinkhi, Marwan and Kolyvanov, Klim and Street, Lena Annika and Preibisch, Stephan and Ercan, Sevin{\c c}} } @article {69602, title = {Data Release: High-Resolution Imaging and Segmentation of P7 Mouse Tissue Microarchitecture Using FIB-SEM and Machine Learning}, journal = {bioRxiv}, year = {2024}, month = {2024 Sep 07}, abstract = {

This report presents a comprehensive data release exploring the tissue microarchitecture of P7 aged mice using Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) combined with machine learning-based segmentations of nuclei. The study includes high-resolution 3D volumes and nucleus segmentations for seven vital tissues{\textemdash}pancreas, liver, kidney, heart, thymus, hippocampus, and skin{\textemdash}from a single mouse. The detailed datasets are openly accessible on OpenOrganelle.org, providing a valuable resource for the scientific community to support further research and collaboration.

}, doi = {10.1101/2024.09.05.611438}, url = {https://www.doi.org/10.1101/2024.09.05.611438}, author = {Ackerman, David and Avetissian, Emma and Bleck, Christopher K. E. and Bogovic, John A. and Innerberger, Michael and Korff, Wyatt and Li, Wei-Ping and Lu, Zhiyuan and Petruncio, Alyson and Preibisch, Stephan and Qiu, Wei and Jeff L Rhoades and Saalfeld, Stephan and Silva, Malan and Trautman, Eric T. and Vorimo, Rebecca and Weigel, Aubrey and Yu, Zhiheng and Zubov, Yurii and ,} } @article {68807, title = {Architecture and dynamics of a desmosome-endoplasmic reticulum complex.}, journal = {Nature Cell Biology}, volume = {25}, year = {2023}, month = {2023 Jun 16}, pages = {823-835}, abstract = {

The endoplasmic reticulum (ER) forms a dynamic network that contacts other cellular membranes to regulate stress responses, calcium signalling and lipid transfer. Here, using high-resolution volume electron microscopy, we find that the ER forms a previously unknown association with keratin intermediate filaments and desmosomal cell-cell junctions. Peripheral ER assembles into mirror image-like arrangements at desmosomes and exhibits nanometre proximity to keratin filaments and the desmosome cytoplasmic plaque. ER tubules exhibit stable associations with desmosomes, and perturbation of desmosomes or keratin filaments alters ER organization, mobility and expression of ER stress transcripts. These findings indicate that desmosomes and the keratin cytoskeleton regulate the distribution, function and dynamics of the ER network. Overall, this study reveals a previously unknown subcellular architecture defined by the structural integration of ER tubules with an epithelial intercellular junction.

}, keywords = {Cytoskeleton, Desmosomes, Endoplasmic Reticulum, Intermediate Filaments, Keratins}, issn = {1476-4679}, doi = {10.1038/s41556-023-01154-4}, author = {Bharathan, Navaneetha Krishnan and Giang, William and Hoffman, Coryn L and Aaron, Jesse S and Khuon, Satya and Chew, Teng-Leong and Preibisch, Stephan and Trautman, Eric T and Heinrich, Larissa and Bogovic, John and Bennett, Davis and Ackerman, David and Park, Woohyun and Petruncio, Alyson and Weigel, Aubrey V and Saalfeld, Stephan and Wayne Vogl, A and Stahley, Sara N and Kowalczyk, Andrew P} } @article {68587, title = {Automated reconstruction of whole-embryo cell lineages by learning from sparse annotations.}, journal = {Nature Biotechnology}, volume = {41}, year = {2023}, month = {2023 Jan 01}, pages = {44-49}, abstract = {

We present a method to automatically identify and track nuclei in time-lapse microscopy recordings of entire developing embryos. The method combines deep learning and global optimization. On a mouse dataset, it reconstructs 75.8\% of cell lineages spanning 1 h, as compared to 31.8\% for the competing method. Our approach improves understanding of where and when cell fate decisions are made in developing embryos, tissues, and organs.

}, keywords = {Animals, Blastocyst, Cell Lineage, Embryo, Mammalian, Mice, Microscopy}, issn = {1546-1696}, doi = {10.1038/s41587-022-01427-7}, author = {Malin-Mayor, Caroline and Hirsch, Peter and Guignard, Leo and McDole, Katie and Wan, Yinan and Lemon, William C and Kainmueller, Dagmar and Keller, Philipp J and Preibisch, Stephan and Funke, Jan} } @article {68313, title = {Automated reconstruction of whole-embryo cell lineages by learning from sparse annotations.}, journal = {Nature Biotechnology}, year = {2022}, month = {2022 Sep 05}, abstract = {

We present a method to automatically identify and track nuclei in time-lapse microscopy recordings of entire developing embryos. The method combines deep learning and global optimization. On a mouse dataset, it reconstructs 75.8\% of cell lineages spanning 1 h, as compared to 31.8\% for the competing method. Our approach improves understanding of where and when cell fate decisions are made in developing embryos, tissues, and organs.

}, issn = {1546-1696}, doi = {10.1038/s41587-022-01427-7}, author = {Malin-Mayor, Caroline and Hirsch, Peter and Guignard, Leo and McDole, Katie and Wan, Yinan and Lemon, William C and Kainmueller, Dagmar and Keller, Philipp J and Preibisch, Stephan and Funke, Jan} } @article {69715, title = {Best practice standards for circular RNA research}, journal = {Nature Methods}, volume = {19}, year = {2022}, month = {05/2022}, pages = {1208 - 1220}, abstract = {

Circular RNAs (circRNAs) are formed in all domains of life and via different mechanisms. There has been an explosion in the number of circRNA papers in recent years; however, as a relatively young field, circRNA biology has an urgent need for common experimental standards for isolating, analyzing, expressing and depleting circRNAs. Here we propose a set of guidelines for circRNA studies based on the authors{\textquoteright} experience. This Perspective will specifically address the major class of circRNAs in Eukarya that are generated by a spliceosome-catalyzed back-splicing event. We hope that the implementation of best practice principles for circRNA research will help move the field forward and allow a better functional understanding of this fascinating group of RNAs.

}, issn = {1548-7091}, doi = {10.1038/s41592-022-01487-2}, url = {https://www.nature.com/articles/s41592-022-01487-2https://www.nature.com/articles/s41592-022-01487-2.pdfhttps://www.nature.com/articles/s41592-022-01487-2.pdfhttps://www.nature.com/articles/s41592-022-01487-2}, author = {Nielsen, Anne F. and Bindereif, Albrecht and Bozzoni, Irene and Hanan, Mor and Hansen, Thomas B. and Irimia, Manuel and Kadener, Sebastian and Kristensen, Lasse S. and Legnini, Ivano and Morlando, Mariangela and Jarlstad Olesen, Morten T. and Pasterkamp, R. Jeroen and Preibisch, Stephan and Rajewsky, Nikolaus and Suenkel, Christin and Kjems, J{\o}rgen} } @article {68462, title = {Cap-dependent translation initiation monitored in living cells.}, journal = {Nature Communications}, volume = {13}, year = {2022}, month = {2022 Nov 02}, pages = {6558}, abstract = {

mRNA translation is tightly regulated to preserve cellular homeostasis. Despite extensive biochemical, genetic, and structural studies, a detailed understanding of mRNA translation regulation is lacking. Imaging methodologies able to resolve the binding dynamics of translation factors at single-cell and single-mRNA resolution were necessary to fully elucidate regulation of this paramount process. Here live-cell spectroscopy and single-particle tracking were combined to interrogate the binding dynamics of endogenous initiation factors to the 5{\textquoteright}cap. The diffusion of initiation factors (IFs) changed markedly upon their association with mRNA. Quantifying their diffusion characteristics revealed the sequence of IFs assembly and disassembly in cell lines and the clustering of translation in neurons. This approach revealed translation regulation at high spatial and temporal resolution that can be applied to the formation of any endogenous complex that results in a measurable shift in diffusion.

}, keywords = {Peptide Chain Initiation, Translational, Peptide Initiation Factors, Protein Biosynthesis, RNA Caps, RNA, Messenger}, issn = {2041-1723}, doi = {10.1038/s41467-022-34052-8}, author = {Gandin, Valentina and English, Brian P and Freeman, Melanie and Leroux, Louis-Philippe and Preibisch, Stephan and Walpita, Deepika and Jaramillo, Maritza and Singer, Robert H} } @article {69714, title = {FRC-QE: a robust and comparable 3D microscopy image quality metric for cleared organoids.}, journal = {Bioinformatics}, volume = {37}, year = {2021}, month = {03/2021}, pages = {3088-3090}, abstract = {

SUMMARY: Here, we propose Fourier ring correlation-based quality estimation (FRC-QE) as a new metric for automated image quality estimation in 3D fluorescence microscopy acquisitions of cleared organoids that yields comparable measurements across experimental replicates, clearing protocols and works for different microscopy modalities.

AVAILABILITY AND IMPLEMENTATION: FRC-QE is written in ImgLib2/Java and provided as an easy-to-use and macro-scriptable plugin for Fiji. Code, documentation, sample images and further information can be found under https://github.com/PreibischLab/FRC-QE.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

}, keywords = {Imaging, Three-Dimensional, Microscopy, Fluorescence, Software}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btab160}, author = {Preusser, Friedrich and Dos Santos, Nat{\'a}lia and Contzen, J{\"o}rg and Stachelscheid, Harald and Costa, {\'E}rico Tosoni and Mergenthaler, Philipp and Preibisch, Stephan} } @article {67792, title = {Light sheet fluorescence microscopy.}, journal = {Nature Reviews Methods Primers}, volume = {1}, year = {2021}, month = {2021 Nov 03}, abstract = {

Light sheet fluorescence microscopy (LSFM) uses a thin sheet of light to excite only fluorophores within the focal volume. Light sheet microscopes (LSMs) have a true optical sectioning capability and, hence, provide axial resolution, restrict photobleaching and phototoxicity to a fraction of the sample and use cameras to record tens to thousands of images per second. LSMs are used for in-depth analyses of large, optically cleared samples and long-term three-dimensional (3D) observations of live biological specimens at high spatio-temporal resolution. The independently operated illumination and detection trains and the canonical implementations, selective/single plane illumination microscope (SPIM) and digital scanned laser microscope (DSLM), are the basis for many LSM designs. In this Primer, we discuss various applications of LSFM for imaging multicellular specimens, developing vertebrate and invertebrate embryos, brain and heart function, 3D cell culture models, single cells, tissue sections, plants, organismic interaction and entire cleared brains. Further, we describe the combination of LSFM with other imaging approaches to allow for super-resolution or increased penetration depth and the use of sophisticated spatio-temporal manipulations to allow for observations along multiple directions. Finally, we anticipate developments of the field in the near future.

}, doi = {10.1038/s43586-021-00069-4}, url = {https://www.nature.com/articles/s43586-021-00069-4}, author = {Stelzer, Ernst H. K. and Strobl, Frederic and Chang, Bo-Jui and Preusser, Friedrich and Preibisch, Stephan and McDole, Katie and Fiolka, Reto} } @article {65079, title = {BigStitcher: reconstructing high-resolution image datasets of cleared and expanded samples.}, journal = {Nature Methods}, volume = {16}, year = {2019}, month = {2019 Sep}, pages = {870-74}, abstract = {

Light-sheet imaging of cleared and expanded samples creates terabyte-sized datasets that consist of many unaligned three-dimensional image tiles, which must be reconstructed before analysis. We developed the BigStitcher software to address this challenge. BigStitcher enables interactive visualization, fast and precise alignment, spatially resolved quality estimation, real-time fusion and deconvolution of dual-illumination, multitile, multiview datasets. The software also compensates for optical effects, thereby improving accuracy and enabling subsequent biological analysis.

}, issn = {1548-7091}, doi = {10.1038/s41592-019-0501-0}, url = {http://www.nature.com/articles/s41592-019-0501-0http://www.nature.com/articles/s41592-019-0501-0.pdfhttp://www.nature.com/articles/s41592-019-0501-0.pdfhttp://www.nature.com/articles/s41592-019-0501-0}, author = {H{\"o}rl, David and Rojas Rusak, Fabio and Preusser, Friedrich and Tillberg, Paul and Randel, Nadine and Chhetri, Raghav K. and Cardona, Albert and Keller, Philipp J. and Harz, Hartmann and Leonhardt, Heinrich and Treier, Mathias and Preibisch, Stephan} } @article {49535, title = {Brain-wide circuit interrogation at the cellular level guided by online analysis of neuronal function.}, journal = {Nature Methods}, volume = {15}, year = {2018}, month = {2018 Nov 30}, pages = {1117-1125}, abstract = {

Whole-brain imaging allows for comprehensive functional mapping of distributed neural pathways, but neuronal perturbation experiments are usually limited to targeting predefined regions or genetically identifiable cell types. To complement whole-brain measures of activity with brain-wide manipulations for testing causal interactions, we introduce a system that uses measuredactivity patterns to guide optical perturbations of any subset of neurons in the same fictively behaving larval zebrafish. First, a light-sheet microscope collects whole-brain data that are rapidly analyzed by a distributed computing system to generate functional brain maps. On the basis of these maps, the experimenter can then optically ablate neurons and image activity changes across the brain. We applied this method to characterize contributions of behaviorally tuned populations to the optomotor response. We extended the system to optogenetically stimulate arbitrary subsets of neurons during whole-brain imaging. These open-source methods enable delineating the contributions of neurons to brain-wide circuit dynamics and behavior in individual animals.

}, doi = {10.1038/s41592-018-0221-x}, author = {Vladimirov, Nikita and Wang, Chen and H{\"o}ckendorf, Burkhard and Pujala, Avinash and Tanimoto, Masashi and Mu, Yu and Yang, Chao-Tsung and Wittenbach, Jason and Freeman, Jeremy and Preibisch, Stephan and Koyama, Minoru and Keller, Philipp J and Ahrens, Misha B} } @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 {46925, title = {Nuclear accessibility of β-actin mRNA is measured by 3D single-molecule real-time tracking.}, journal = {Journal of Cell Biology}, volume = {209}, year = {2015}, month = {2015 May 25}, pages = {609-19}, abstract = {

Imaging single proteins or RNAs allows direct visualization of the inner workings of the cell. Typically, three-dimensional (3D) images are acquired by sequentially capturing a series of 2D sections. The time required to step through the sample often impedes imaging of large numbers of rapidly moving molecules. Here we applied multifocus microscopy (MFM) to instantaneously capture 3D single-molecule real-time images in live cells, visualizing cell nuclei at 10 volumes per second. We developed image analysis techniques to analyze messenger RNA (mRNA) diffusion in the entire volume of the nucleus. Combining MFM with precise registration between fluorescently labeled mRNA, nuclear pore complexes, and chromatin, we obtained globally optimal image alignment within 80-nm precision using transformation models. We show that β-actin mRNAs freely access the entire nucleus and fewer than 60\% of mRNAs are more than 0.5 {\textmu}m away from a nuclear pore, and we do so for the first time accounting for spatial inhomogeneity of nuclear organization.

}, issn = {1540-8140}, doi = {10.1083/jcb.201411032}, author = {Smith, Carlas S and Preibisch, Stephan and Joseph, Aviva and Abrahamsson, Sara and Rieger, Bernd and Myers, Eugene and Singer, Robert H and Grunwald, David} } @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} } @article {6962, title = {Efficient Bayesian-based multiview deconvolution.}, journal = {Nature Methods}, volume = {11}, year = {2014}, month = {2014 Apr 20}, pages = {645-8}, abstract = {

Light-sheet fluorescence microscopy is able to image large specimens with high resolution by capturing the samples from multiple angles. Multiview deconvolution can substantially improve the resolution and contrast of the images, but its application has been limited owing to the large size of the data sets. Here we present a Bayesian-based derivation of multiview deconvolution that drastically improves the convergence time, and we provide a fast implementation using graphics hardware.

}, issn = {1548-7105}, doi = {10.1038/nmeth.2929}, author = {Preibisch, Stephan and Amat, Fernando and Stamataki, Evangelia and Sarov, Mihail and Singer, Robert H and Myers, Eugene 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} } @article {5684, title = {TrakEM2 software for neural circuit reconstruction.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e38011}, abstract = {

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.

}, keywords = {Animals, Models, Nerve Net, Neuroimaging, Neurological, Neurons, Software, Synapses, Synaptic Transmission}, issn = {1932-6203}, doi = {10.1371/journal.pone.0038011}, author = {Cardona, Albert and Saalfeld, Stephan and Schindelin, Johannes and Arganda-Carreras, Ignacio and Preibisch, Stephan and Longair, Mark and Tomancak, Pavel and Hartenstein, Volker and Douglas, Rodney J} } @article {46785, title = {TrakEM2 software for neural circuit reconstruction.}, journal = {PLoS One}, volume = {7}, year = {2012}, month = {2012}, pages = {e38011}, abstract = {

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.

}, keywords = {Animals, Models, Neurological, Nerve Net, Neuroimaging, Neurons, Software, Synapses, Synaptic Transmission}, issn = {1932-6203}, doi = {10.1371/journal.pone.0038011}, author = {Cardona, Albert and Saalfeld, Stephan and Schindelin, Johannes and Arganda-Carreras, Ignacio and Preibisch, Stephan and Longair, Mark and Tomancak, Pavel and Hartenstein, Volker and Douglas, Rodney J} } @article {5687, title = {An integrated micro- and macroarchitectural analysis of the Drosophila brain by computer-assisted serial section electron microscopy.}, journal = {PLoS Biology}, volume = {8}, year = {2010}, month = {2010}, abstract = {

The analysis of microcircuitry (the connectivity at the level of individual neuronal processes and synapses), which is indispensable for our understanding of brain function, is based on serial transmission electron microscopy (TEM) or one of its modern variants. Due to technical limitations, most previous studies that used serial TEM recorded relatively small stacks of individual neurons. As a result, our knowledge of microcircuitry in any nervous system is very limited. We applied the software package TrakEM2 to reconstruct neuronal microcircuitry from TEM sections of a small brain, the early larval brain of Drosophila melanogaster. TrakEM2 enables us to embed the analysis of the TEM image volumes at the microcircuit level into a light microscopically derived neuro-anatomical framework, by registering confocal stacks containing sparsely labeled neural structures with the TEM image volume. We imaged two sets of serial TEM sections of the Drosophila first instar larval brain neuropile and one ventral nerve cord segment, and here report our first results pertaining to Drosophila brain microcircuitry. Terminal neurites fall into a small number of generic classes termed globular, varicose, axiform, and dendritiform. Globular and varicose neurites have large diameter segments that carry almost exclusively presynaptic sites. Dendritiform neurites are thin, highly branched processes that are almost exclusively postsynaptic. Due to the high branching density of dendritiform fibers and the fact that synapses are polyadic, neurites are highly interconnected even within small neuropile volumes. We describe the network motifs most frequently encountered in the Drosophila neuropile. Our study introduces an approach towards a comprehensive anatomical reconstruction of neuronal microcircuitry and delivers microcircuitry comparisons between vertebrate and insect neuropile.

}, keywords = {Animals, Brain, Computer-Assisted, Drosophila melanogaster, Electron, Humans, Image Processing, Imaging, Microscopy, Neurons, Neuropil, Software, Synapses, Three-Dimensional, Transmission}, issn = {1545-7885}, doi = {10.1371/journal.pbio.1000502}, author = {Cardona, Albert and Saalfeld, Stephan and Preibisch, Stephan and Schmid, Benjamin and Cheng, Anchi and Pulokas, Jim and Tomancak, Pavel and Hartenstein, Volker.} } @proceedings {46792, title = {Into ImgLib{\textemdash}Generic image processing in Java}, year = {2010}, month = {2012 Oct 27}, address = {Mondorf-les-Bains, Luxembourg}, abstract = {

The purpose of ImgLib, a Generic Java Image Processing Library, is to provide an abstract framework enabling Java developers to design and implement data processing algorithms without having to consider dimensionality, type of data (e. g. byte, float, complex float), or strategies for data access (e. g. linear arrays, cells, paged cells). This kind of programming has significant advantages over the classical way. An algorithm written once for a certain class of Type will potentially run on any compatible Type, even if it does not exist yet. Same applies for data access strategies and the number of dimensions.
We achieve this abstraction by accessing data through Iterators and Type interfaces. Iterators guarantee efficient traversal through pixels depending on whether random coordinate access is required or just all pixels have to be visited once, whether real or integer coordinates are accessed, whether coordinates outside of image boundaries are accessed or not. Type interfaces define the supported operators on pixel values (like basic algebra) and hide the underlying basic type from algorithm implementation.

}, author = {Preibisch, Stephan and Tomancak, Pavel and Saalfeld, Stephan} } @article {46161, title = {Software for bead-based registration of selective plane illumination microscopy data.}, journal = {Nature Methods}, volume = {7}, year = {2010}, month = {2010 Jun}, pages = {418-9}, keywords = {Animals, Caenorhabditis elegans, Drosophila melanogaster, Imaging, Three-Dimensional, Lighting, Microscopy, Software}, issn = {1548-7105}, doi = {10.1038/nmeth0610-418}, author = {Preibisch, Stephan and Saalfeld, Stephan and Schindelin, Johannes and Tomancak, Pavel} } @proceedings {46793, title = {Bead-based mosaicing of single plane illumination microscopy images using geometric local descriptor matching.}, volume = {7259}, year = {2009}, month = {2009 Mar 27}, pages = {72592S}, publisher = {SPIE}, address = {Lake Buena Vista, FL}, abstract = {

Single Plane Illumination Microscopy (SPIM) is an emerging microscopic technique that enables live imaging of large biological specimens in their entirety. By imaging the biological sample from multiple angles, SPIM has the potential to achieve isotropic resolution throughout relatively large biological specimens. For every angle, however, only a shallow section of the specimen is imaged with high resolution, whereas deeper regions appear increasingly blurred. Existing intensity-based registration techniques still struggle to robustly and accurately align images that are characterized by limited overlap and/or heavy blurring. To be able to register such images, we add sub-resolution fluorescent beads to the rigid agarose medium in which the imaged specimen is embedded. For each segmented bead, we store the relative location of its n nearest neighbors in image space as rotation-invariant geometric local descriptors. Corresponding beads between overlapping images are identified by matching these descriptors. The bead correspondences are used to simultaneously estimate the globally optimal transformation for each individual image. The final output image is created by combining all images in an angle-independent output space, using volume injection and local content-based weighting of contributing images. We demonstrate the performance of our approach on data acquired from living embryos of Drosophila and fixed adult C.elegans worms. Bead-based registration outperformed intensity-based registration in terms of computation speed by two orders of magnitude while producing bead registration errors below 1 μm (about 1 pixel). It, therefore, provides an ideal tool for processing of long term time-lapse recordings of embryonic development consisting of hundreds of time points.

}, doi = {10.1117/12.812612}, author = {Preibisch, Stephan and Saalfeld, Stephan and Rohlfing, Torsten and Tomancak, Pavel} } @article {46786, title = {Globally optimal stitching of tiled 3D microscopic image acquisitions.}, journal = {Bioinformatics}, volume = {25}, year = {2009}, month = {2009 Jun 1}, pages = {1463-5}, abstract = {

MOTIVATION: Modern anatomical and developmental studies often require high-resolution imaging of large specimens in three dimensions (3D). Confocal microscopy produces high-resolution 3D images, but is limited by a relatively small field of view compared with the size of large biological specimens. Therefore, motorized stages that move the sample are used to create a tiled scan of the whole specimen. The physical coordinates provided by the microscope stage are not precise enough to allow direct reconstruction (Stitching) of the whole image from individual image stacks.

RESULTS: To optimally stitch a large collection of 3D confocal images, we developed a method that, based on the Fourier Shift Theorem, computes all possible translations between pairs of 3D images, yielding the best overlap in terms of the cross-correlation measure and subsequently finds the globally optimal configuration of the whole group of 3D images. This method avoids the propagation of errors by consecutive registration steps. Additionally, to compensate the brightness differences between tiles, we apply a smooth, non-linear intensity transition between the overlapping images. Our stitching approach is fast, works on 2D and 3D images, and for small image sets does not require prior knowledge about the tile configuration.

AVAILABILITY: The implementation of this method is available as an ImageJ plugin distributed as a part of the Fiji project (Fiji is just ImageJ: http://pacific.mpi-cbg.de/).

}, keywords = {Animals, Drosophila, Imaging, Three-Dimensional, Larva, Microscopy, Confocal}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btp184}, author = {Preibisch, Stephan and Saalfeld, Stephan and Tomancak, Pavel} } @proceedings {46795, title = {Fast stitching of large 3d biological datasets.}, year = {2008}, month = {2008 Nov 7}, address = {Luxembourg}, abstract = {

In order to study anatomy of organisms with high-resolution there is an increasing demand to image large specimen in three dimensions (3D). Confocal microscopy is able to produce high-resolution 3D images, but these are limited by its relatively small field of view compared to the size of large biological specimens. To overcome this drawback, motorized stages moving the sample are used to create a tiled scan of the whole specimen. The physical coordinates provided by the microscope stage are not precise enough to allow reconstruction ({\textquotedblright}Stitching{\textquotedblright}) of the whole image from individual image stacks.
We developed an algorithm, as well as an ImageJ plug-in, based on the Fourier Shift Theorem that computes all possible translations (x, y, z) between two 3D images at once, yielding the best overlap in terms of the cross correlation measure. Apart from the obvious gain in computation time it has the advantage that it cannot be trapped in local minima as it simply computes all possible solutions. Computing the overlap between two adjacent image stacks is fast (12 seconds for two 512x512x89 images on a Intel {\textregistered} Core2Duo with 2.2GHz) making it suitable for real time use, i.e. computing the output image during acquisition of the individual image stacks.
To compensate the possible shading- and brightness differences we apply a smooth linear intensity transition between the overlapping stacks. Additionally we extended the to generic 3D registration using gradient based rotation detection on top of the phase correlation method. We demonstrate the performance of our 3D stitching plug-in on several tiled confocal images and show an example of its application for 3D registration.

}, author = {Preibisch, Stephan and Saalfeld, Stephan and Tomancak, Pavel} }