Accession Number : ADA289213

Title :   Computer-Aided Breast Cancer Diagnosis.

Descriptive Note : Master's thesis,

Corporate Author : AIR FORCE INST OF TECH WRIGHT-PATTERSON AFB OH SCHOOL OF ENGINEERING

Personal Author(s) : Kocur, Catherine M.

PDF Url : ADA289213

Report Date : DEC 1994

Pagination or Media Count : 112

Abstract : This research advances computer-aided breast cancer diagnosis. More than 50 million women over the age of 40 are currently at risk from this disease in the United States. Computer-aided diagnosis is offered as a second opinion to radiologists to aid in decreasing the number of false readings of mammograms. This automated tool is designed to enhance detection and classification. New feature extraction methods are presented that provide increased classification power. Angular second moment, a second-order gray-level histogram statistic, provides baseline accuracy. Two novel extraction methods, eigenmass and wavelets, are introduced to the field. Based on the Karhunen-Loeve Transform, eigenmass features are developed using eigenvectors to alter the data set into new coefficients. Wavelets, previously only exploited for their segmentation benefits, are explored as features for classification. Daubechies-4, Danbechies-2O, and biorthogonal wavelets are each investigated. Applied to 94 difficult-to-diagnosis digitized microcalcification cases, performance is 74 percent correct classifications. Feature selection techniques are presented which further improve performance. Statistical analysis, neural and decision boundary-based methods are implemented, compared, and validated to isolate and remove useless features. The contribution from this analysis is an increase to 88 percent correct classification in system performance.

Descriptors :   *DETECTION, *COMPUTER AIDED DIAGNOSIS, *CANCER, *MAMMARY GLANDS, DATA BASES, IMAGE PROCESSING, RISK, EIGENVECTORS, NEOPLASMS, ACCURACY, THESES, BASE LINES, EXTRACTION, STATISTICAL ANALYSIS, WOMEN, HISTOGRAMS, CALCIFICATION, BIOPSY.

Subject Categories : Anatomy and Physiology
      Medicine and Medical Research
      Cybernetics

Distribution Statement : APPROVED FOR PUBLIC RELEASE