F F Yin1, M L Giger, C J Vyborny, K Doi, R A Schmidt. 1. Kurt Rossmann Laboratories for Radiologic Imaging Research, Department of Radiology, University of Chicago, IL 60637.
Abstract
RATIONALE AND OBJECTIVES: Identification of regions as possible masses on digitized screen film mammograms is an important initial step in the computerized detection of breast carcinomas. Possible masses may be initially extracted using criteria based on optical densities, geometric patterns, and asymmetries between corresponding locations in right and left mammograms. In this study, the usefulness of information arising from mammographic asymmetries for the identification of mass lesions is investigated. METHODS: Two techniques are investigated--a nonlinear bilateral-subtraction technique based on image pairs and a local gray-level thresholding technique based on single images. Detection performances obtained with the two techniques in combination with various feature-analysis techniques are evaluated using 154 pairs of mammograms and compared using free-response receiver operating characteristic (FROC) analysis. RESULTS: The nonlinear bilateral-subtraction technique performed better than the local gray-level thresholding technique. CONCLUSION: The incorporation of asymmetric information appears to be useful for computerized identification of possible masses on mammograms.
RATIONALE AND OBJECTIVES: Identification of regions as possible masses on digitized screen film mammograms is an important initial step in the computerized detection of breast carcinomas. Possible masses may be initially extracted using criteria based on optical densities, geometric patterns, and asymmetries between corresponding locations in right and left mammograms. In this study, the usefulness of information arising from mammographic asymmetries for the identification of mass lesions is investigated. METHODS: Two techniques are investigated--a nonlinear bilateral-subtraction technique based on image pairs and a local gray-level thresholding technique based on single images. Detection performances obtained with the two techniques in combination with various feature-analysis techniques are evaluated using 154 pairs of mammograms and compared using free-response receiver operating characteristic (FROC) analysis. RESULTS: The nonlinear bilateral-subtraction technique performed better than the local gray-level thresholding technique. CONCLUSION: The incorporation of asymmetric information appears to be useful for computerized identification of possible masses on mammograms.
Authors: E D Pisano; S Zong; B M Hemminger; M DeLuca; R E Johnston; K Muller; M P Braeuning; S M Pizer Journal: J Digit Imaging Date: 1998-11 Impact factor: 4.056
Authors: E D Pisano; J Chandramouli; B M Hemminger; D Glueck; R E Johnston; K Muller; M P Braeuning; D Puff; W Garrett; S Pizer Journal: J Digit Imaging Date: 1997-11 Impact factor: 4.056
Authors: E D Pisano; J Chandramouli; B M Hemminger; M DeLuca; D Glueck; R E Johnston; K Muller; M P Braeuning; S Pizer Journal: J Digit Imaging Date: 1997-05 Impact factor: 4.056
Authors: José Celaya-Padilla; Antonio Martinez-Torteya; Juan Rodriguez-Rojas; Jorge Galvan-Tejada; Victor Treviño; José Tamez-Peña Journal: Biomed Res Int Date: 2015-07-09 Impact factor: 3.411