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Proceedings Paper

Statistical modeling of oriented line patterns in mammograms
Author(s): Tim C. Parr; Christopher J. Taylor; Susan M. Astley; Caroline R. M. Boggis
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Paper Abstract

Malignant breast lesions in x-ray mammograms are often characterized by abnormal patterns of linear structures. Architectural distortions and stellate lesions are examples of patterns frequently presenting with an appearance of radiating linear structures. Attempts to automatically detect these abnormalities have generally concentrated on features of known importance, such as radiating linear structure concurrency, spread of focus and radial distance. We present an alternative statistically based representation that is both complete and uncommitted. Our representation places no emphasis on the features known to be important, yet clearly incorporates them. We present results for an experiment in which 92% of 9600 lesion/non-lesion pixels were classified correctly. Using a set of 150 high resolution digitized mammograms a lesion detection sensitivity of 80% was obtained at a specificity of 0.38 false positives per image.

Paper Details

Date Published: 25 April 1997
PDF: 12 pages
Proc. SPIE 3034, Medical Imaging 1997: Image Processing, (25 April 1997); doi: 10.1117/12.274159
Show Author Affiliations
Tim C. Parr, Univ. of Manchester (United Kingdom)
Christopher J. Taylor, Univ. of Manchester (United Kingdom)
Susan M. Astley, Univ. of Manchester (United Kingdom)
Caroline R. M. Boggis, North West Regional Training Ctr. for Breast Screening (United Kingdom)

Published in SPIE Proceedings Vol. 3034:
Medical Imaging 1997: Image Processing
Kenneth M. Hanson, Editor(s)

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