Literature DB >> 24318825

Segmentation and quantitative analysis of individual cells in developmental tissues.

Kaustav Nandy1, 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.

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Year:  2014        PMID: 24318825     DOI: 10.1007/978-1-60327-292-6_16

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

1.  Design and evaluation of an accurate CNR-guided small region iterative restoration-based tumor segmentation scheme for PET using both simulated and real heterogeneous tumors.

Authors:  Alpaslan Koç; Albert Güveniş
Journal:  Med Biol Eng Comput       Date:  2019-12-17       Impact factor: 2.602

2.  Automated Identification and Localization of Hematopoietic Stem Cells in 3D Intravital Microscopy Data.

Authors:  Reema A Khorshed; Edwin D Hawkins; Delfim Duarte; Mark K Scott; Olufolake A Akinduro; Narges M Rashidi; Martin Spitaler; Cristina Lo Celso
Journal:  Stem Cell Reports       Date:  2015-06-25       Impact factor: 7.765

  2 in total

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