Share Email Print

Proceedings Paper

Computer-aided diagnosis of lesions on multimodality images of the breast
Author(s): Maryellen Lissak Giger; Zhimin Huo; Karla Horsch; Edward R. Hendrick; Luz A. Venta; Carl J. Vyborny; Ioana R. Bonta; Li Lan
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

We have developed computerized methods for the analysis of lesions that combine results from different imaging modalities, in this case digitized mammograms and sonograms of the breast, for distinguishing between malignant and benign lesions. The computerized classification method -- applied here to mass lesions seen on both digitized mammograms and sonograms, includes: (1) automatic lesion extraction, (2) automated feature extraction, and (3) automatic classification. The results for both modalities are then merged into an estimate of the likelihood of malignancy. For the mammograms, computer-extracted lesion features include degree of spiculation, margin sharpness, lesion density, and lesion texture. For the ultrasound images, lesion features include margin definition, texture, shape, and posterior acoustic attenuation. Malignant and benign lesions are better distinguished when features from both mammograms and ultrasound images are combined.

Paper Details

Date Published: 3 July 2001
PDF: 5 pages
Proc. SPIE 4322, Medical Imaging 2001: Image Processing, (3 July 2001); doi: 10.1117/12.431141
Show Author Affiliations
Maryellen Lissak Giger, Univ. of Chicago (United States)
Zhimin Huo, Univ. of Chicago (United States)
Karla Horsch, Univ. of Chicago (United States)
Edward R. Hendrick, Northwestern Univ. (United States)
Luz A. Venta, Northwestern Univ. (United States)
Carl J. Vyborny, Univ. of Chicago (United States)
Ioana R. Bonta, Univ. of Chicago (United States)
Li Lan, Univ. of Chicago (United States)

Published in SPIE Proceedings Vol. 4322:
Medical Imaging 2001: Image Processing
Milan Sonka; Kenneth M. Hanson, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?