Related Experiment Video
Updated: Aug 26, 2026

Using Rapid Serial Visual Presentation to Measure Set-Specific Capture, a Consequence of Distraction While Multitasking
Published on: August 29, 2018
Computer-aided detection schemes: the effect of limiting the number of cued regions in each case
Bin Zheng1, Joseph K Leader, Gordon Abrams
1Department of Radiology, Imaging Research, Magee-Women's Hospital, University of Pittsburgh, 300 Halket St., Ste. 4200, Pittsburgh, PA 15213-3180, USA. zhengb@msx.upmc.edu
Objective:
We assessed performance changes of a mammographic computer-aided detection scheme when we restricted the maximum number of regions that could be identified (cued) as showing positive findings in each case.
Materials And Methods:
A computer-aided detection scheme was applied to 500 cases (or 2,000 images), including 300 cases in which mammograms showed verified malignant masses. We evaluated the overall case-based performance of the scheme using a free-response receiver operating characteristic approach, and we measured detection sensitivity at a fixed false-positive detection rate of 0.4 per image after gradually reducing the maximum number of cued regions allowed for each case from seven to one.
Results:
The original computer-aided detection scheme achieved a maximum case-based sensitivity of 97% at 3.3 false-positive detected regions per image. For a detection decision score set at 0.565, the scheme had a 79% (237/300) case-based sensitivity, with 0.4 false-positive detected regions per image. After limiting the number of maximum allowed cued regions per case, the false-positive rates decreased faster than the true-positive rates. At a maximum of two cued regions per case, the false-positive rate decreased from 0.4 to 0.21 per image, whereas detection sensitivity decreased from 237 to 220 masses. To maintain sensitivity at 79%, we reduced the detection decision score to as low as 0.36, which resulted in a reduction of false-positive detected regions from 0.4 to 0.3 per image and a reduction in region-based sensitivity from 66.1% to 61.4%.
Conclusion:
Limiting the maximum number of cued regions per case can improve the overall case-based performance of computer-aided detection schemes in mammography.

