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Proceedings Paper

Automatic segmentation and measurement of cells in 3-D
Author(s): Laura N. Mascio; Damir Sudar
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Paper Abstract

Three-dimensional (3D) data are obtained on biological cells by collecting optical slices at different depths in the cell using confocal laser scanning microscopy. A method has been developed which allows such three-dimensional data to be automatically segmented so that objects within the cell can be identified and labelled. Segmentation allows an object in a field to be recognized as distinct from other objects and from the background. This is done using an algorithm which performs a cell-dependent sequence of image processing functions on each slice of the image data (2D). Identification requires that a single object be recognized as one entity through all of the slices of data (3D). This is done with a 3D labelling routine. In this application, cell nuclei are first defined in 3D, and then structures within them (i.e. chromosome domains) can be identified. Measurements are made on these domains for the purpose of determining the relationship between chromosomal locations and the possibility that they will exchange genetic information.

Paper Details

Date Published: 1 July 1990
PDF: 9 pages
Proc. SPIE 1206, New Technologies in Cytometry and Molecular Biology, (1 July 1990); doi: 10.1117/12.17810
Show Author Affiliations
Laura N. Mascio, Lawrence Livermore National Lab. (United States)
Damir Sudar, Lawrence Livermore National Lab. (United States)


Published in SPIE Proceedings Vol. 1206:
New Technologies in Cytometry and Molecular Biology
Gary C. Salzman, Editor(s)

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