Paper
31 July 2002 Computer-aided detection of microcalcifications in digital mammograms using a synthetic technique
Ruiping Wang, Baikun Wan, Zhenhe Ma, Xuchen Cao
Author Affiliations +
Proceedings Volume 4875, Second International Conference on Image and Graphics; (2002) https://doi.org/10.1117/12.477210
Event: Second International Conference on Image and Graphics, 2002, Hefei, China
Abstract
Clustered microcalcifications (MCCs) on mammograms are important hints of breast cancer. Nevertheless, it is a complex and difficult task for radiologists to detect the clustered MCCs from the tissue background of mammograms only by naked eyes. This paper presents a method for computer-aided detection of MCCs in digital mammograms. The detection algorithm mainly consists of two different methods. The first one, based on the difference-image technique, recognizes high-frequency signals and very high-frequency noise. The second one is able to extract high-frequency signal by exploiting a wavelet based noise suppression and neural network (NN) classification. In the false-positive reduction step, false signals are separated from MCCs by means of an AND operation on signals from two methods. The algorithm is tested with a series of clinical mammograms. A sensitivity ofmore than 90% is obtained at a relatively low false-positive (FP) detection of 2.18 per image. The results are compared with thejudgement ofradiological experts, and they are very encouraging.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ruiping Wang, Baikun Wan, Zhenhe Ma, and Xuchen Cao "Computer-aided detection of microcalcifications in digital mammograms using a synthetic technique", Proc. SPIE 4875, Second International Conference on Image and Graphics, (31 July 2002); https://doi.org/10.1117/12.477210
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KEYWORDS
Mammography

Wavelets

Denoising

Neural networks

Interference (communication)

Breast

Image processing

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