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Proceedings Paper

Fractal discrimination of MRI breast masses using multiple segmentations
Author(s): Alan I. Penn; Scott F. Thompson; Mitchell D. Schnall; Murray H. Loew; Lizann Bolinger
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Paper Abstract

Fractal dimension (fd) of lesion borders has been proposed as a feature to discriminate between malignant and benign masses on MR breast images. The fd value is computed using a sample space of fractal models, an approach that reduces sensitivity to signal noise and image variability. The user specifies a rectangular region of interest (ROI) around the mass and the algorithm generates a segmentation zone from the ROI. Fractal models are constructed on multiple threshold intensity contours within the segmentation zone. Preliminary results show that the combination of statistical fd feature and expert-observer interpretations improves separation of benign from malignant breast masses when compared to expert-observer interpretations alone. The statistical fd feature has been incorporated into a prototype computer-aided-diagnosis (CAD) system that outputs the following to assist the diagnostician in determining clinical action: (1) A likelihood-of-cancer measure computed from fd and reader interpretations, (2) A binary categorical value indicating whether a test case is fd- highly suspicious or fd-inconclusive, (3) The ROI with portions of the mass border with the most cancer-like fractal characteristics highlighted.

Paper Details

Date Published: 6 June 2000
PDF: 8 pages
Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); doi: 10.1117/12.387599
Show Author Affiliations
Alan I. Penn, Alan Penn & Associates, Inc., Univ. of Pennsylvania, and George Washington Univ. (United States)
Scott F. Thompson, Alan Penn & Associates, Inc. (United States)
Mitchell D. Schnall, Univ. of Pennsylvania (United States)
Murray H. Loew, George Washington Univ. (United States)
Lizann Bolinger, Univ. of Iowa (United States)


Published in SPIE Proceedings Vol. 3979:
Medical Imaging 2000: Image Processing
Kenneth M. Hanson, Editor(s)

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