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Automated detection of Breast Asymmetries
Author(s) -
I Peter Miller,
Sue Astley
Publication year - 1993
Publication title -
citeseer x (the pennsylvania state university)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5244/c.7.52
Subject(s) - asymmetry , artificial intelligence , computer science , segmentation , computer vision , brightness , pattern recognition (psychology) , image segmentation , breast cancer , sign (mathematics) , cancer , mathematics , medicine , physics , mathematical analysis , quantum mechanics , optics
Breast asymmetry is an important radiological sign of cancer. This paper describes the first approach aiming to detect all types of asymmetry; previous asymmetrybased research has been focussed on the detection of mass lesions. The conventional approach is to search for brightness or texture differences between corresponding locations on left and right breast images. Due to the difficulty in accurately identifying corresponding locations, asymmetry cues generated in this way are insufficiently specific to be used as prompts for small and subtle abnormalities in a computer-aided diagnosis system. We have undertaken studies to discover more about the visual cues utilized by radiologists. As a result, we propose a new automatic method for detecting asymmetry based on the comparison of corresponding anatomical structures, identified by an automatic segmentation of breast tissue types. We describe methods for comparing the shape and brightness distribution of these regions, and we present results obtained by combining evidence for asymmetry.

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