Accession Number : ADA326304

Title :   Classification of Microcalcifications of the Diagnosis of Breast Cancer Using Artificial Neural Networks.

Descriptive Note : Annual rept. 1 Sep 95-31 Aug 96,

Corporate Author : GEORGETOWN UNIV WASHINGTON DC

Personal Author(s) : Wu, Yuzheng C.

PDF Url : ADA326304

Report Date : SEP 1996

Pagination or Media Count : 31

Abstract : Early detection of breast cancer depends on the accurate classification of microcalcifications. We have developed a computer vision system that can classify microcalcifications objectively and consistently to aid radiologists in the diagnosis of breast cancer. A convolution neural network (CNN) was employed to classify benign and malignant microcalcifications in the radiographs of pathological specimen that were digitized at a high resolution.

Descriptors :   *NEURAL NETS, *CALCIFICATION, *BREAST CANCER, DETECTION, ACCURACY, HIGH RESOLUTION, CLASSIFICATION, COMPUTER AIDED DIAGNOSIS, RADIOGRAPHY, CONVOLUTION.

Subject Categories : Medicine and Medical Research
      Cybernetics
      Optics

Distribution Statement : APPROVED FOR PUBLIC RELEASE