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Proceedings Paper

Texture analysis and tissue segmentation of cryosection images
Author(s): Tamara S. Williams; Jennifer L. Casper
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Paper Abstract

This paper outlines the exploration of two methods to detect texture in a digital cryosection image from the Visible Human Project. For the purpose of this research, texture is defined as a regular or irregular placement of color in an image. A higher-level decision-making algorithm was employed to extract different body tissues: fat, muscle, and bone. This algorithm was designed on the premise that each body tissue has a different visible texture. Another method utilized an artificial intelligence approach, a neural net, to extract textured tissues. Each problem demands a unique neural net; hence, this neural net is customized in terms of the image dataset and the goal of texture detection.

Paper Details

Date Published: 21 May 1999
PDF: 8 pages
Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); doi: 10.1117/12.348500
Show Author Affiliations
Tamara S. Williams, Gustavus Adolphus College (United States)
Jennifer L. Casper, Univ. of Wisconsin/La Crosse (United States)

Published in SPIE Proceedings Vol. 3661:
Medical Imaging 1999: Image Processing
Kenneth M. Hanson, Editor(s)

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