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
Distribution Statement : APPROVED FOR PUBLIC RELEASE