Share Email Print

Proceedings Paper

Computer-aided detection of breast masses on full-field digital mammograms: false positive reduction using gradient field analysis
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Several full-field digital mammography (FFDM) systems have been approved for clinical applications. It is important to develop a CAD system that can easily be adapted to images acquired by FFDM systems from different manufacturers. To develop a CAD system that is independent of the FFDM manufacturer's proprietary preprocessing methods, we used the raw FFDM image as input and developed a multi-resolution preprocessing scheme for image enhancement. Our CAD system performed prescreening to identify mass candidates, segmented the suspicious structures, extracted morphological and texture features, and then classified masses and normal tissue. In this study, we investigated the use of a two-stage gradient field analysis to identify suspicious masses, and the effectiveness of a new gradient field feature extracted from each suspicious object for false positive (FP) reduction. A data set of 104 cases with 243 images acquired with a GE FFDM system was collected. Most cases had two mammographic views, except for 12 cases that had three views and 1 case with only one view. The data set contained 106 masses. The true locations of the masses were identified by an experienced radiologist. Using free-response receiver operating characteristic (FROC) analysis, it was found that our CAD system achieved a cased-based sensitivity of 70%, 80%, and 88% at 0.8, 1.3, and 1.7 FP marks/image, respectively. The high performance indicated the usefulness of the new gradient field analysis method.

Paper Details

Date Published: 12 May 2004
PDF: 7 pages
Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004); doi: 10.1117/12.536126
Show Author Affiliations
Jun Wei, Univ. of Michigan (United States)
Berkman Sahiner, Univ. of Michigan (United States)
Lubomir M. Hadjiiski, Univ. of Michigan (United States)
Heang-Ping Chan, Univ. of Michigan (United States)
Nicholas Petrick, FDA Ctr. for Devices and Radiological Health (United States)
Mark A. Helvie, Univ. of Michigan (United States)
Chuan Zhou, Univ. of Michigan (United States)
Zhanyu Ge, Univ. of Michigan (United States)

Published in SPIE Proceedings Vol. 5370:
Medical Imaging 2004: Image Processing
J. Michael Fitzpatrick; Milan Sonka, 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?