Literature DB >> 22872081

A computational image analysis glossary for biologists.

Adrienne H K Roeder1, Alexandre Cunha, Michael C Burl, Elliot M Meyerowitz.   

Abstract

Recent advances in biological imaging have resulted in an explosion in the quality and quantity of images obtained in a digital format. Developmental biologists are increasingly acquiring beautiful and complex images, thus creating vast image datasets. In the past, patterns in image data have been detected by the human eye. Larger datasets, however, necessitate high-throughput objective analysis tools to computationally extract quantitative information from the images. These tools have been developed in collaborations between biologists, computer scientists, mathematicians and physicists. In this Primer we present a glossary of image analysis terms to aid biologists and briefly discuss the importance of robust image analysis in developmental studies.

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Year:  2012        PMID: 22872081     DOI: 10.1242/dev.076414

Source DB:  PubMed          Journal:  Development        ISSN: 0950-1991            Impact factor:   6.868


  17 in total

1.  Digital Single-Cell Analysis of Plant Organ Development Using 3DCellAtlas.

Authors:  Thomas D Montenegro-Johnson; Petra Stamm; Soeren Strauss; Alexander T Topham; Michail Tsagris; Andrew T A Wood; Richard S Smith; George W Bassel
Journal:  Plant Cell       Date:  2015-04-21       Impact factor: 11.277

2.  Accuracy in Quantitative 3D Image Analysis.

Authors:  George W Bassel
Journal:  Plant Cell       Date:  2015-03-24       Impact factor: 11.277

3.  Versatile method for quantifying and analyzing morphological differences in experimentally obtained images.

Authors:  Kristine S Bagdassarian; Katherine A Connor; Ian H Jermyn; J Peter Etchells
Journal:  Plant Signal Behav       Date:  2019-11-24

Review 4.  Let's push things forward: disruptive technologies and the mechanics of tissue assembly.

Authors:  Victor D Varner; Celeste M Nelson
Journal:  Integr Biol (Camb)       Date:  2013-09       Impact factor: 2.192

5.  Learn to segment single cells with deep distance estimator and deep cell detector.

Authors:  Weikang Wang; David A Taft; Yi-Jiun Chen; Jingyu Zhang; Callen T Wallace; Min Xu; Simon C Watkins; Jianhua Xing
Journal:  Comput Biol Med       Date:  2019-04-08       Impact factor: 4.589

6.  Computer Vision and Less Complex Image Analyses to Monitor Potato Traits in Fields.

Authors:  Junfeng Gao; Jesper Cairo Westergaard; Erik Alexandersson
Journal:  Methods Mol Biol       Date:  2021

7.  Integrated Cells and Collagen Fibers Spatial Image Analysis.

Authors:  Georgii Vasiukov; Tatiana Novitskaya; Maria-Fernanda Senosain; Alex Camai; Anna Menshikh; Pierre Massion; Andries Zijlstra; Sergey Novitskiy
Journal:  Front Bioinform       Date:  2021-11-08

8.  Live imaging, identifying, and tracking single cells in complex populations in vivo and ex vivo.

Authors:  Minjung Kang; Panagiotis Xenopoulos; Silvia Muñoz-Descalzo; Xinghua Lou; Anna-Katerina Hadjantonakis
Journal:  Methods Mol Biol       Date:  2013

Review 9.  Investigating epithelial-to-mesenchymal transition with integrated computational and experimental approaches.

Authors:  Jianhua Xing; Xiao-Jun Tian
Journal:  Phys Biol       Date:  2019-03-07       Impact factor: 2.583

Review 10.  Artificial intelligence and algorithmic computational pathology: an introduction with renal allograft examples.

Authors:  Alton B Farris; Juan Vizcarra; Mohamed Amgad; Lee A D Cooper; David Gutman; Julien Hogan
Journal:  Histopathology       Date:  2021-03-08       Impact factor: 5.087

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