Detection of mammographic masses using sector features with a multiple-circular-path neural network

Shih-Chung Benedict Lo; Huai Li; Akira Hasegawa; Yue J. Wang; Matthew T. Freedman M.D.; Seong Ki Mun

doi:10.1117/12.310848

24 June 1998 Detection of mammographic masses using sector features with a multiple-circular-path neural network

Shih-Chung Benedict Lo, Huai Li, Akira Hasegawa, Yue J. Wang, Matthew T. Freedman M.D., Seong Ki Mun

Proceedings Volume 3338, Medical Imaging 1998: Image Processing; (1998) https://doi.org/10.1117/12.310848
Event: Medical Imaging '98, 1998, San Diego, CA, United States

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.

Citation Download Citation

Shih-Chung Benedict Lo, Huai Li, Akira Hasegawa, Yue J. Wang, Matthew T. Freedman M.D., and Seong Ki Mun "Detection of mammographic masses using sector features with a multiple-circular-path neural network", Proc. SPIE 3338, Medical Imaging 1998: Image Processing, (24 June 1998); https://doi.org/10.1117/12.310848

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