Computer-Aided Detection of Mammographic Masses in Dense Breast Images
Abstract
This document describes the research tasks and educational activities in which the PI has been engaged during the first phase of this post-doctoral work. The Pr has selected 342 dense breast masses (175 cancer cases and 167 benign cases) for testing using an automated segmentation algorithm which combines region growing with cost function analysis. This method has been validated on 198 cases using overlap, accuracy, sensitivity and specificity statistics by one expert radiologist and has been validated on 46 cases by a second expert radiologist. All statistics have values that range from 0 to 1. The mean overlap and accuracy values for cancer cases are approximately 0.46 and 0.78, respectively. The mean overlap and accuracy values for benign cases are approximately 0.52 and 0.87, respectively. The PI has attended cancer imaging workshops, attended two scientific meetings, made two oral presentations, team taught an Imaging Technologies course, and published two manuscripts during this time.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jun 01, 2004
- Accession Number
- ADA427116
Entities
People
- Lisa M. Kinnard
Organizations
- Howard University