Fractal discrimination of MRI breast masses using multiple segmentations

Alan I. Penn; Scott F. Thompson; Mitchell D. Schnall; Murray H. Loew; Lizann Bolinger

doi:10.1117/12.387599

6 June 2000 Fractal discrimination of MRI breast masses using multiple segmentations

Alan I. Penn, Scott F. Thompson, Mitchell D. Schnall, Murray H. Loew, Lizann Bolinger

Author Affiliations +

Proceedings Volume 3979, Medical Imaging 2000: Image Processing; (2000) https://doi.org/10.1117/12.387599
Event: Medical Imaging 2000, 2000, San Diego, CA, United States

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.

Citation Download Citation

Alan I. Penn, Scott F. Thompson, Mitchell D. Schnall, Murray H. Loew, and Lizann Bolinger "Fractal discrimination of MRI breast masses using multiple segmentations", Proc. SPIE 3979, Medical Imaging 2000: Image Processing, (6 June 2000); https://doi.org/10.1117/12.387599

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE