Focus

Focus on Bioimage Informatics

Explosive growth in the size and complexity of microscopy-based imaging data and the need to extract more quantitative data from it increasingly requires sophisticated image acquisition and analysis methods and software tools. A collection of articles discusses the role of bioimage informatics in microscopy, specific tools that are available, and the challenges and opportunities in the field.

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Editorial

Focus on Bioimage Informatics

The quest for quantitative microscopy

doi:10.1038/nmeth.2102

With the aid of informatics, microscopy is in the midst of a crucial evolution into a more quantitative and powerful technique.


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This Month

Focus on Bioimage Informatics

The Author File: Robert F. Murphy

Monya Baker

doi:10.1038/nmeth.2088

Creating algorithms to turn images into cell models.


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Correspondence

Focus on Bioimage Informatics

OMERO.searcher: content-based image search for microscope images

Baek Hwan Cho, Ivan Cao-Berg, Jennifer Ann Bakal & Robert F Murphy

doi:10.1038/nmeth.2086


Focus on Bioimage Informatics

SimuCell: a flexible framework for creating synthetic microscopy images

Satwik Rajaram, Benjamin Pavie, Nicholas E F Hac, Steven J Altschuler & Lani F Wu

doi:10.1038/nmeth.2096


Focus on Bioimage Informatics

PhenoRipper: software for rapidly profiling microscopy images

Satwik Rajaram, Benjamin Pavie, Lani F Wu & Steven J Altschuler

doi:10.1038/nmeth.2097


Focus on Bioimage Informatics

Annotated high-throughput microscopy image sets for validation

Vebjorn Ljosa, Katherine L Sokolnicki & Anne E Carpenter

doi:10.1038/nmeth.2083


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Commentary

Focus on Bioimage Informatics

Why bioimage informatics matters

Gene Myers

doi:10.1038/nmeth.2024

Driven by the importance of spatial and physical factors in cellular processes and the size and complexity of modern image data, computational analysis of biological imagery has become a vital emerging sub-discipline of bioinformatics and computer vision.


Focus on Bioimage Informatics

Current challenges in open-source bioimage informatics

Albert Cardona & Pavel Tomancak

doi:10.1038/nmeth.2082

We discuss the advantages and challenges of the open-source strategy in biological image analysis and argue that its full impact will not be realized without better support and recognition of software engineers’ contributions to the biological sciences and more support of this development model from funders and institutions.


Focus on Bioimage Informatics

A call for bioimaging software usability

Anne E Carpenter, Lee Kamentsky & Kevin W Eliceiri

doi:10.1038/nmeth.2073

Bioimaging software developed in a research setting often is not widely used by the scientific community. We suggest that, to maximize both the public’s and researchers’ investments, usability should be a more highly valued goal. We describe specific characteristics of usability toward which bioimaging software projects should aim.


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Historical Commentary

Focus on Bioimage Informatics

NIH Image to ImageJ: 25 years of image analysis

Caroline A Schneider, Wayne S Rasband & Kevin W Eliceiri

doi:10.1038/nmeth.2089

For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.


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Perspectives

Focus on Bioimage Informatics

Fiji: an open-source platform for biological-image analysis

Johannes Schindelin, Ignacio Arganda-Carreras, Erwin Frise, Verena Kaynig, Mark Longair, Tobias Pietzsch, Stephan Preibisch, Curtis Rueden, Stephan Saalfeld, Benjamin Schmid, Jean-Yves Tinevez, Daniel James White, Volker Hartenstein, Kevin Eliceiri, Pavel Tomancak & Albert Cardona

doi:10.1038/nmeth.2019

Presented is an overview of the image-analysis software platform Fiji, a distribution of ImageJ that updates the underlying ImageJ architecture and adds modern software design elements to expand the capabilities of the platform and facilitate collaboration between biologists and computer scientists.


Focus on Bioimage Informatics

BioImageXD: an open, general-purpose and high-throughput image-processing platform

Pasi Kankaanpää, Lassi Paavolainen, Silja Tiitta, Mikko Karjalainen, Joacim Päivärinne, Jonna Nieminen, Varpu Marjomäki, Jyrki Heino & Daniel J White

doi:10.1038/nmeth.2047

Described is BioImageXD, a simple, user-friendly, open-source platform for biological image analysis. The authors outline their design criteria and how BioImageXD meets them, and demonstrate BioImageXD performance in a study of integrin clustering.


Focus on Bioimage Informatics

Icy: an open bioimage informatics platform for extended reproducible research

Fabrice de Chaumont, Stéphane Dallongeville, Nicolas Chenouard, Nicolas Hervé, Sorin Pop, Thomas Provoost, Vannary Meas-Yedid, Praveen Pankajakshan, Timothée Lecomte, Yoann Le Montagner, Thibault Lagache, Alexandre Dufour & Jean-Christophe Olivo-Marin

doi:10.1038/nmeth.2075

Icy is a collaborative platform for biological image analysis that extends reproducible research principles by facilitating and stimulating the contribution and sharing of algorithm-based tools and protocols between researchers.


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Review

Focus on Bioimage Informatics

Biological imaging software tools

Kevin W Eliceiri, Michael R Berthold, Ilya G Goldberg, Luis Ibàñez, B S Manjunath, Maryann E Martone, Robert F Murphy, Hanchuan Peng, Anne L Plant, Badrinath Roysam, Nico Stuurmann, Jason R Swedlow, Pavel Tomancak & Anne E Carpenter

doi:10.1038/nmeth.2084

Representative members of the bioimage informatics community review the computational steps and some of the primary software tools available to biologists who are acquiring and analyzing microscopy-based digital image data, with a focus on open-source options.


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Brief Communications

Focus on Bioimage Informatics

Unsupervised modeling of cell morphology dynamics for time-lapse microscopy

Qing Zhong, Alberto Giovanni Busetto, Juan P Fededa, Joachim M Buhmann & Daniel W Gerlich

doi:10.1038/nmeth.2046

The authors present a bioinformatic method for the accurate unsupervised classification of time-lapse images. This method should enable reproducible and unbiased annotation of large-scale image data sets.


Focus on Bioimage Informatics

An image analysis toolbox for high-throughput C. elegans assays

Carolina Wählby, Lee Kamentsky, Zihan H Liu, Tammy Riklin-Raviv, Annie L Conery, Eyleen J O'Rourke, Katherine L Sokolnicki, Orane Visvikis, Vebjorn Ljosa, Javier E Irazoqui, Polina Golland, Gary Ruvkun, Frederick M Ausubel & Anne E Carpenter

doi:10.1038/nmeth.1984

The freely available WormToolbox enables high-throughput image analysis of a variety of phenotypes of Caenorhabditis elegans in liquid culture and should prove useful for image-based screens.


Focus on Bioimage Informatics

Elastic volume reconstruction from series of ultra-thin microscopy sections

Stephan Saalfeld, Richard Fetter, Albert Cardona & Pavel Tomancak

doi:10.1038/nmeth.2072

The authors describe a method for realigning images from serially sectioned biological specimens that minimizes the effect of artificial deformations in the alignment by applying global elastic constraints. The method is applied to transmission electron microscopy and array tomography image series and is made available through the Fiji platform.


Focus on Bioimage Informatics

Faster STORM using compressed sensing

Lei Zhu, Wei Zhang, Daniel Elnatan & Bo Huang

doi:10.1038/nmeth.1978

Global optimization of single-molecule localizations using compressed sensing allows stochastic optical reconstruction microscopy (STORM) at high molecular densities and live cell super-resolution imaging with a temporal resolution of 3 seconds.


Focus on Bioimage Informatics

Rapid, accurate particle tracking by calculation of radial symmetry centers

Raghuveer Parthasarathy

doi:10.1038/nmeth.2071

An analytically exact approach that determines the radial symmetry center of the image of any radially symmetric particle allows faster localization than iterative methods while also giving localization accuracies approaching theoretical limits.


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Article

Focus on Bioimage Informatics

ViBE-Z: a framework for 3D virtual colocalization analysis in zebrafish larval brains

Olaf Ronneberger, Kun Liu, Meta Rath, Dominik Rueβ, Thomas Mueller, Henrik Skibbe, Benjamin Drayer, Thorsten Schmidt, Alida Filippi, Roland Nitschke, Thomas Brox, Hans Burkhardt & Wolfgang Driever

doi:10.1038/nmeth.2076

An imaging and registration framework called Virtual Brain Explorer for Zebrafish (ViBE-Z) allows mapping of gene expression patterns and anatomical structures in the zebrafish larval brain. ViBE-Z is provided via a web interface and contains software for image processing, data sets from several developmental stages and a brain atlas.


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