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Computer-Aided Detection Schemes: The Effect of Limiting the Number of Cued Regions in Each Case

¹ All authors: Department of Radiology, Imaging Research, Magee-Women's Hospital, University of Pittsburgh, 300 Halket St., Ste. 4200, Pittsburgh, PA 15213-3180.

View larger version (13K): [in a new window]   Fig. 1. —Bar graph shows size distribution of 300 masses depicted in data set. Mass size is represented by larger depicted area on either craniocaudal or mediolateral oblique mammographic view.

View larger version (11K): [in a new window]   Fig. 2. —Bar graph shows distribution of subjectively rated subtlety of 300 masses depicted in data set. Subtlety of each identified mass was rated on 5-point scale, ranging from 1 (very easily visible) to 5 (very subtly visible). Mass subtlety is represented by lower-rated depiction on either craniocaudal or mediolateral oblique mammographic view.

View larger version (13K): [in a new window]   Fig. 3. —Graph illustrates overall performance of computer-aided detection scheme when applied to database of 2,000 mammograms (500 cases) with no limitation on number of cued regions. Detection decision threshold line is represented by dotted line. = case-based free-response receiver operating characteristic curve, = image-based free-response receiver operating characteristic curve.

View larger version (14K): [in a new window]   Fig. 4. —Graph shows five plots depicting free-response receiver operating characteristic curves generated by different maximum numbers of cued regions allowed per case. Maximum number of cued regions indicated by = no limit, = 7, = 5, = 3, = 2.

View larger version (9K): [in a new window]   Fig. 5. —Scatterplot shows sizes and subtlety ratings distributions for 34 masses that were undetected by both case-based and image-based scoring methods. = no limit to number of regions in each case that may be cued as showing positive findings, = maximum number of regions that may be cued is 2.

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