New results in computer-aided diagnosis (CAD) of breast cancer using a recently developed SVM/GRNN Oracle hybrid

Walker H. Land Jr.; Lut Wong; Daniel W. McKee; Timothy Masters; Frances R. Anderson; Anurag Raturi; Joseph Y. Lo

doi:10.1117/12.533142

12 May 2004 New results in computer-aided diagnosis (CAD) of breast cancer using a recently developed SVM/GRNN Oracle hybrid

Walker H. Land Jr., Lut Wong, Daniel W. McKee, Timothy Masters, Frances R. Anderson, Anurag Raturi, Joseph Y. Lo

Author Affiliations +

Proceedings Volume 5370, Medical Imaging 2004: Image Processing; (2004) https://doi.org/10.1117/12.533142
Event: Medical Imaging 2004, 2004, San Diego, California, United States

Abstract

Breast cancer is second only to lung cancer as a tumor-related cause of death in women. Currently, the method of choice for the early detection of breast cancer is mammography. While sensitive to the detection of non palpable breast lesions, its positive predictive value (PPV) is low, resulting in biopsies that are only 15%-34% likely to reveal malignancy. This paper explores the use of a recently designed Support Vector Machine (SVM)/Generalized Regression Neural Network (GRNN) Oracle hybrid to classify breast lesions and evaluate the software's performance as an interpretive aid to radiologists. The main objective of the research was to perform an independent analysis, using a new, integrated film screen mammogram data base of approximately 2500 cases from five separate institutions, to verify results obtained previously[14]. This study demonstrated the following: (1) The DE crossover constant has little, if any, effect on measures of performance (MOP). (2) A specificity of approximately 5.6% is achieved at 100% sensitivity, which increases to approximately 36% at 95% sensitivity. (3) PPV increases from 51% to 56% as sensitivity is decreased from 100 to 95%, respectively.

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Walker H. Land Jr., Lut Wong, Daniel W. McKee, Timothy Masters, Frances R. Anderson, Anurag Raturi, and Joseph Y. Lo "New results in computer-aided diagnosis (CAD) of breast cancer using a recently developed SVM/GRNN Oracle hybrid", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); https://doi.org/10.1117/12.533142

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