Hybrid technique for detection of microcalcification clusters in mammograms

Howard C. Choe; Gary C. McCord; Andrew K. Chan

doi:10.1117/12.304920

26 March 1998 Hybrid technique for detection of microcalcification clusters in mammograms

Howard C. Choe, Gary C. McCord, Andrew K. Chan

Proceedings Volume 3391, Wavelet Applications V; (1998) https://doi.org/10.1117/12.304920
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

The introduction of wavelets in signal and image processing has provided a new tool to create innovative and novel methods for solving problems in the areas of data compression, signal analysis, and nose removal, to name a few. Although wavelets are popular and used extensively in research and in engineering applications, their use in signature detection and classification is still an area open to extensive investigation. This paper discusses wavelet image processing working in synergy with other processing techniques to detect and recognize abnormal and cueing signature that are important to diagnostic medicine - detection and recognition of microcalcification clusters in mammograms. In this application, an innovative detection algorithm that takes advantage of wavelet multiresolution analysis and synthesis is developed to assist radiologists looking for clusters of microcalcification in digitized mammograms. Microcalcification regions may not be detectable by visual inspection or other detection techniques because of their inherent complexity. The algorithm presented in this paper successfully unmasks the complexity and limits the false positives. A thorough analysis, algorithm description and examples are shown in this paper.

Citation Download Citation

Howard C. Choe, Gary C. McCord, and Andrew K. Chan "Hybrid technique for detection of microcalcification clusters in mammograms", Proc. SPIE 3391, Wavelet Applications V, (26 March 1998); https://doi.org/10.1117/12.304920

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