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5 April 2007 Computerized mass detection in whole breast ultrasound images: reduction of false positives using bilateral subtraction technique
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Abstract
The comparison of left and right mammograms is a common technique used by radiologists for the detection and diagnosis of masses. In mammography, computer-aided detection (CAD) schemes using bilateral subtraction technique have been reported. However, in breast ultrasonography, there are no reports on CAD schemes using comparison of left and right breasts. In this study, we propose a scheme of false positive reduction based on bilateral subtraction technique in whole breast ultrasound images. Mass candidate regions are detected by using the information of edge directions. Bilateral breast images are registered with reference to the nipple positions and skin lines. A false positive region is detected based on a comparison of the average gray values of a mass candidate region and a region with the same position and same size as the candidate region in the contralateral breast. In evaluating the effectiveness of the false positive reduction method, three normal and three abnormal bilateral pairs of whole breast images were employed. These abnormal breasts included six masses larger than 5 mm in diameter. The sensitivity was 83% (5/6) with 13.8 (165/12) false positives per breast before applying the proposed reduction method. By applying the method, false positives were reduced to 4.5 (54/12) per breast without removing a true positive region. This preliminary study indicates that the bilateral subtraction technique is effective for improving the performance of a CAD scheme in whole breast ultrasound images.
© (2007) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuji Ikedo, Daisuke Fukuoka, Takeshi Hara, Hiroshi Fujita, Etsuo Takada, Tokiko Endo M.D., and Takako Morita "Computerized mass detection in whole breast ultrasound images: reduction of false positives using bilateral subtraction technique", Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 65141T (5 April 2007); https://doi.org/10.1117/12.709225
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