Literature DB >> 22118455

Computer vision in cell biology.

Gaudenz Danuser1.   

Abstract

Computer vision refers to the theory and implementation of artificial systems that extract information from images to understand their content. Although computers are widely used by cell biologists for visualization and measurement, interpretation of image content, i.e., the selection of events worth observing and the definition of what they mean in terms of cellular mechanisms, is mostly left to human intuition. This Essay attempts to outline roles computer vision may play and should play in image-based studies of cellular life.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22118455     DOI: 10.1016/j.cell.2011.11.001

Source DB:  PubMed          Journal:  Cell        ISSN: 0092-8674            Impact factor:   41.582


  49 in total

Review 1.  Toward the virtual cell: automated approaches to building models of subcellular organization "learned" from microscopy images.

Authors:  Taráz E Buck; Jieyue Li; Gustavo K Rohde; Robert F Murphy
Journal:  Bioessays       Date:  2012-07-10       Impact factor: 4.345

2.  Current challenges in open-source bioimage informatics.

Authors:  Albert Cardona; Pavel Tomancak
Journal:  Nat Methods       Date:  2012-06-28       Impact factor: 28.547

3.  Automated line scan analysis to quantify biosensor activity at the cell edge.

Authors:  R J Allen; D Tsygankov; J S Zawistowski; T C Elston; K M Hahn
Journal:  Methods       Date:  2013-08-30       Impact factor: 3.608

4.  Extensible visualization and analysis for multidimensional images using Vaa3D.

Authors:  Hanchuan Peng; Alessandro Bria; Zhi Zhou; Giulio Iannello; Fuhui Long
Journal:  Nat Protoc       Date:  2014-01-02       Impact factor: 13.491

5.  Systematic quantification of developmental phenotypes at single-cell resolution during embryogenesis.

Authors:  Julia L Moore; Zhuo Du; Zhirong Bao
Journal:  Development       Date:  2013-08       Impact factor: 6.868

6.  Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis.

Authors:  Antony Lee; Konstantinos Tsekouras; Christopher Calderon; Carlos Bustamante; Steve Pressé
Journal:  Chem Rev       Date:  2017-04-17       Impact factor: 60.622

7.  Imagining the future of bioimage analysis.

Authors:  Erik Meijering; Anne E Carpenter; Hanchuan Peng; Fred A Hamprecht; Jean-Christophe Olivo-Marin
Journal:  Nat Biotechnol       Date:  2016-12-07       Impact factor: 54.908

Review 8.  Imaging and modeling the dynamics of clathrin-mediated endocytosis.

Authors:  Marcel Mettlen; Gaudenz Danuser
Journal:  Cold Spring Harb Perspect Biol       Date:  2014-08-28       Impact factor: 10.005

Review 9.  Biomarkers identified with time-lapse imaging: discovery, validation, and practical application.

Authors:  Alice A Chen; Lei Tan; Vaishali Suraj; Renee Reijo Pera; Shehua Shen
Journal:  Fertil Steril       Date:  2013-03-15       Impact factor: 7.329

10.  Cell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes.

Authors:  Mark-Anthony Bray; Shantanu Singh; Han Han; Chadwick T Davis; Blake Borgeson; Cathy Hartland; Maria Kost-Alimova; Sigrun M Gustafsdottir; Christopher C Gibson; Anne E Carpenter
Journal:  Nat Protoc       Date:  2016-08-25       Impact factor: 13.491

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