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Proceedings Paper

Detection of mammographic masses using sector features with a multiple-circular-path neural network
Author(s): Shih-Chung Benedict Lo; Huai Li; Akira Hasegawa; Yue J. Wang; Matthew T. Freedman M.D.; Seong Ki Mun
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Paper Abstract

In the clinical course of detecting masses, mammographers usually evaluate the surrounding background of a radiodense when breast cancer is suspected. In this study, we adapted this fundamental concept and computed features of the suspicious region in radial sections. These features were then arranged by circular convolution processes within a neural network, which led to an improvement in detecting mammographic masses.

Paper Details

Date Published: 24 June 1998
PDF: 10 pages
Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); doi: 10.1117/12.310848
Show Author Affiliations
Shih-Chung Benedict Lo, Georgetown Univ. Medical Ctr. (United States)
Huai Li, Odyssey Technologies Inc. (United States)
Akira Hasegawa, Tokyo Institute of Technology (United States)
Yue J. Wang, Georgetown Univ. Medical Ctr. and Catholic Univ. of America (United States)
Matthew T. Freedman M.D., Georgetown Univ. Medical Ctr. (United States)
Seong Ki Mun, Georgetown Univ. Medical Ctr. (United States)

Published in SPIE Proceedings Vol. 3338:
Medical Imaging 1998: Image Processing
Kenneth M. Hanson, Editor(s)

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