Segmentation and Quantitative Analysis of Individual Cells in Developmental Tissues View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2014

AUTHORS

Kaustav Nandy , Jusub Kim , Dean P. McCullough , Matthew McAuliffe , Karen J. Meaburn , Terry P. Yamaguchi , Prabhakar R. Gudla , Stephen J. Lockett

ABSTRACT

Image analysis is vital for extracting quantitative information from biological images and is used extensively, including investigations in developmental biology. The technique commences with the segmentation (delineation) of objects of interest from 2D images or 3D image stacks and is usually followed by the measurement and classification of the segmented objects. This chapter focuses on the segmentation task and here we explain the use of ImageJ, MIPAV (Medical Image Processing, Analysis, and Visualization), and VisSeg, three freely available software packages for this purpose. ImageJ and MIPAV are extremely versatile and can be used in diverse applications. VisSeg is a specialized tool for performing highly accurate and reliable 2D and 3D segmentation of objects such as cells and cell nuclei in images and stacks. More... »

PAGES

235-53

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-60327-292-6_16

DOI

http://dx.doi.org/10.1007/978-1-60327-292-6_16

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1001062223

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/24318825


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