Technology for Medical Education, Research, and Disease Screening by Exploitation of Biomarkers in a Large Collection of Uterine Cervix Images

摘要

The Communications Engineering Branch of the National Library of Medicine is collaborating with the National Cancer Institute (NCI) in developing applications for medical education, research, and disease screening for precancer detection in the uterine cervix. These applications include (1) expert marking/labeling of tissue regions, (2) Web viewing/interpretation of histology images, (3) image database/retrieval, and (4) training/testing in clinical image interpretation. Initial NCI studies have been conducted in expert cervicography marking and histology evaluation. We are working toward making cervix images searchable by content-based image retrieval (CBIR). Image pre-processing to remove specular reflection artifacts has achieved 90% success (120 images). Similar results have been obtained for automated location of cervix regions, using Gaussian Mixture Modeling (GMM) with Lab color and one geometric feature. We describe initial classification experiments to discriminate clinically significant tissue, using RGB, HSV, Lab, and YCbCr color models, texture measures, and GMM, Fuzzy C-means, and deterministic annealing algorithms.