title: Segmentation and quantitative analysis of individual cells in developmental tissues.
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.
authors: Optical Microscopy and Analysis Laboratory, SAIC, Frederick National Lab of Cancer Research, NCI, NIH, Frederick, MD, USA.
authors: Kaustav
authors: K
authors: Nandy
authors: Jusub
authors: J
authors: Kim
authors: Dean P
authors: DP
authors: McCullough
authors: Matthew
authors: M
authors: McAuliffe
authors: Karen J
authors: KJ
authors: Meaburn
authors: Terry P
authors: TP
authors: Yamaguchi
authors: Prabhakar R
authors: PR
authors: Gudla
authors: Stephen J
authors: SJ
authors: Lockett
mesh_terms: D002467:Cell Nucleus / Q000235:genetics / Q000648:ultrastructure; D015509:Developmental Biology / Q000295:instrumentation* / Q000379:methods; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D012984:Software