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Proceedings Paper

Segmentation of prostate cancer tissue microarray images
Author(s): Harvey E. Cline; Ali Can; Dirk Padfield
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Paper Abstract

Prostate cancer is diagnosed by histopathology interpretation of hematoxylin and eosin (H and E)-stained tissue sections. Gland and nuclei distributions vary with the disease grade. The morphological features vary with the advance of cancer where the epithelial regions grow into the stroma. An efficient pathology slide image analysis method involved using a tissue microarray with known disease stages. Digital 24-bit RGB images were acquired for each tissue element on the slide with both 10X and 40X objectives. Initial segmentation at low magnification was accomplished using prior spectral characteristics from a training tissue set composed of four tissue clusters; namely, glands, epithelia, stroma and nuclei. The segmentation method was automated by using the training RGB values as an initial guess and iterating the averaging process 10 times to find the four cluster centers. Labels were assigned to the nearest cluster center in red-blue spectral feature space. An automatic threshold algorithm separated the glands from the tissue. A visual pseudo color representation of 60 segmented tissue microarray image was generated where white, pink, red, blue colors represent glands, epithelia, stroma and nuclei, respectively. The higher magnification images provided refined nuclei morphology. The nuclei were detected with a RGB color space principle component analysis that resulted in a grey scale image. The shape metrics such as compactness, elongation, minimum and maximum diameters were calculated based on the eigenvalues of the best-fitting ellipses to the nuclei.

Paper Details

Date Published: 21 February 2006
PDF: 9 pages
Proc. SPIE 6088, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IV, 60880R (21 February 2006); doi: 10.1117/12.643180
Show Author Affiliations
Harvey E. Cline, General Electric Global Research Lab. (United States)
Ali Can, General Electric Global Research Lab. (United States)
Dirk Padfield, General Electric Global Research Lab. (United States)


Published in SPIE Proceedings Vol. 6088:
Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IV
Daniel L. Farkas; Dan V. Nicolau; Robert C. Leif, Editor(s)

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