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11 May 1994 Analysis of false-positive microcalcification clusters identified by a mammographic computer-aided detection scheme
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Abstract
The accuracy of computer-aided detection (CAD) schemes involves a tradeoff between high sensitivity and low false-positive rate. In an on-going study, we are analyzing our CAD scheme for the detection of clustered microcalcifications in digital mammograms to determine the causes of false-negative and false-positive clusters. Two different limitations that lead to false-negatives and false-positives have been identified. The first limitation is imposed by the quality of the digital mammogram, whereas the second is a consequence of the similarities of radiographic features between true and false clusters. In this paper, we examine the effects of image quality, particularly image noise, on the performance of our CAD scheme. Preliminary results indicate that the performance of our scheme is limited by anatomic noise and x-ray quantum noise. Almost all the false positives detected in clinical images by our CAD scheme are caused by a combination of these two forms of noise.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Robert M. Nishikawa, Carl J. Vyborny, Maryellen Lissak Giger, and Kunio Doi "Analysis of false-positive microcalcification clusters identified by a mammographic computer-aided detection scheme", Proc. SPIE 2167, Medical Imaging 1994: Image Processing, (11 May 1994); https://doi.org/10.1117/12.175115
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