Effect of ROI size on the performance of an information-theoretic CAD system in mammography: multi-size fusion analysis

Robert C. Ike III; Swatee Singh; Brian Harrawood; Georgia D. Tourassi

doi:10.1117/12.772678

17 March 2008 Effect of ROI size on the performance of an information-theoretic CAD system in mammography: multi-size fusion analysis

Robert C. Ike III, Swatee Singh, Brian Harrawood, Georgia D. Tourassi

Author Affiliations +

Proceedings Volume 6915, Medical Imaging 2008: Computer-Aided Diagnosis; 691527 (2008) https://doi.org/10.1117/12.772678
Event: Medical Imaging, 2008, San Diego, California, United States

Abstract

Featureless, knowledge-based CAD systems are an attractive alternative to feature-based CAD because they require no to minimal image preprocessing. Such systems compare images directly using the raw image pixel values rather than relying on low-level image features. Specifically, information-theoretic (IT) measures such as mutual information (MI) have been shown to be an effective, featureless, similarity measure for image comparisons. MI captures the statistical relationship between the gray level values of corresponding image pixels. In a CAD system developed at our laboratory, the above concept has been applied for location-specific detection of mammographic masses. The system is designed to operate on a fixed size region of interest (ROI) extracted around a suspicious mammographic location. Since mass sizes vary substantially, there is a potential drawback. When two ROIs are compared, it is unclear how much the parenchymal background contributes in the calculated MI. This uncertainty could deteriorate CAD performance in the extreme cases, namely when a small mass is present in the ROI or when a large mass extends beyond the fixed size ROI. The present study evaluates the effect of ROI size on the overall CAD performance and proposes multisize analysis for possible improvement. Based on two datasets of ROIs extracted from DDSM mammograms, there was a statistically significant decline of the CAD performance as the ROI size increased. The best size ranged between 512x512 and 256x256 pixels. Multisize fusion analysis using a linear model achieved further improvement in CAD performance for both datasets.

Citation Download Citation

Robert C. Ike III, Swatee Singh, Brian Harrawood, and Georgia D. Tourassi "Effect of ROI size on the performance of an information-theoretic CAD system in mammography: multi-size fusion analysis", Proc. SPIE 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 691527 (17 March 2008); https://doi.org/10.1117/12.772678

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available