Share Email Print

Proceedings Paper

Study of adaptability of breast density analysis system developed for screen film mammograms (SFMs) to full-field digital mammograms (FFDMs): robustness of parenchymal texture analysis
Author(s): Jun Wei; Heang-Ping Chan; Mark A. Helvie; Chuan Zhou; Lubomir M. Hadjiiski
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

Mammography is in the transition to full-field digital mammograms (FFDM). It is important to evaluate the adaptability of image analysis methods and computer-aided diagnosis (CAD) systems developed with screen-film mammograms (SFM) to FFDMs. In addition, prior SFMs are more readily available for development of new techniques that involve long-term follow up such as breast cancer risk prediction. We have previously developed a texture-feature-based method for mammographic parenchymal pattern (MPP) analysis on SFMs. The MPP measure was found to be more predictive of breast cancer risk than percent dense area on mammograms. In this study, we investigated the correlation of computerized texture features extracted from matched pairs of SFM and FFDM obtained from the same patient using the same algorithms without retraining for MPP analysis. The computerized texture features from the two modalities demonstrated strong correlation, indicating that the MPP analysis system that we developed with SFMs for breast cancer risk prediction can be readily adapted to FFDMs with at most minor retraining.

Paper Details

Date Published: 8 March 2011
PDF: 6 pages
Proc. SPIE 7963, Medical Imaging 2011: Computer-Aided Diagnosis, 796320 (8 March 2011); doi: 10.1117/12.878235
Show Author Affiliations
Jun Wei, Univ. of Michigan Health System (United States)
Heang-Ping Chan, Univ. of Michigan Health System (United States)
Mark A. Helvie, Univ. of Michigan Health System (United States)
Chuan Zhou, Univ. of Michigan Health System (United States)
Lubomir M. Hadjiiski, Univ. of Michigan Health System (United States)

Published in SPIE Proceedings Vol. 7963:
Medical Imaging 2011: Computer-Aided Diagnosis
Ronald M. Summers M.D.; Bram van Ginneken, Editor(s)

© SPIE. Terms of Use
Back to Top