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Computer-aided detection schemes: the effect of limiting the number of cued regions in each case.

作者信息

Zheng Bin, Leader Joseph K, Abrams Gordon, Shindel Betty, Catullo Victor, Good Walter F, Gur David

机构信息

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

出版信息

AJR Am J Roentgenol. 2004 Mar;182(3):579-83. doi: 10.2214/ajr.182.3.1820579.

DOI:10.2214/ajr.182.3.1820579
PMID:14975949
Abstract

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.

摘要

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