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16 April 1996 Earlier detection of interval breast cancers with adaptive neighborhood contrast enhancement of mammograms
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Abstract
Breast cancer is a leading cause of death among women. Mammography is the best established procedure for breast cancer screening and diagnosis. However, mammograms are hard to interpret even by highly-qualified radiologists, especially in cancers at their early stages. In this paper, we analyze the effectiveness of our adaptive neighborhood contrast enhancement (ANCE) technique in increasing breast cancer diagnosis sensitivity. Two hundred and thirty- three film-screen mammograms of twenty-eight interval cancer patients and six benign control cases were digitized with high-resolution of about 4096 by 2048 by 10-bit pixels and then processed with our ANCE method. Unprocessed and processed digitized mammograms as well as the original films were presented to three reference radiologists for a receiver operating characteristic (ROC) evaluation. The results show that the radiologists' performance with the ANCE-processed images is the best among the three sets of images (original, digitized, and enhanced) in terms of area under the ROC curve, and that diagnostic sensitivity is improved by our ANCE algorithm. All of the 19 interval cancer cases not detected with original films of earlier mammography tests were diagnosed as malignant with the corresponding ANCE- processed versions, while only one of six benign patients initially labeled correctly with the original mammograms was interpreted as malignant after enhancement. This study demonstrates the potential of diagnostic performance improvement for early detection of breast cancer with proper digital image enhancement.
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Liang Shen, Yiping Shen, Rangaraj M. Rangayyan, J. E. Leo Desautels, Heather Bryant, Timothy J. Terry, and Natalka Horeczko "Earlier detection of interval breast cancers with adaptive neighborhood contrast enhancement of mammograms", Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); https://doi.org/10.1117/12.238002
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