Accession Number : ADA328057
Title : Computer-Aided Classification of Malignant and Benign Lesions on Mammograms.
Descriptive Note : Annual rept. 1 May 96-30 Apr 97,
Corporate Author : MICHIGAN UNIV ANN ARBOR
Personal Author(s) : Sahiner, Berkman
PDF Url : ADA328057
Report Date : MAY 1997
Pagination or Media Count : 12
Abstract : In the first year of our project, we have made progress in (1) database collection for mammograms containing masses and microcalcifications; (2) segmentation, transformation, and feature extraction from regions of interest on mammograms containing masses; (3) classifier design for the classification of lesions as malignant or benign; and (4) evaluation of algorithms for classification of masses on mammograms. We have shown that the new image transformation and feature extraction methods improve the mass classification accuracy significantly. We have also shown that, compared to standard feature selection methods, significant improvement can be obtained at the high-sensitivity region of the receiver operating characteristic curve by using a genetic algorithm-based feature selection method.
Descriptors : *CLASSIFICATION, *COMPUTER AIDED DIAGNOSIS, *BREAST CANCER, DATA BASES, ALGORITHMS, IMAGES, TRANSFORMATIONS, LESIONS, HIGH SENSITIVITY, MAMMOGRAPHY.
Subject Categories : Cybernetics
Medicine and Medical Research
Distribution Statement : APPROVED FOR PUBLIC RELEASE