Computer-aided detection of breast masses on prior mammograms

Jun Wei; Berkman Sahiner; Heang-Ping Chan; Lubomir M. Hadjiiski; Marilyn A. Roubidoux; Mark A. Helvie M.D.; Jun Ge; Chuan Zhou; Yi-Ta Wu

doi:10.1117/12.713768

29 March 2007 Computer-aided detection of breast masses on prior mammograms

Jun Wei, Berkman Sahiner, Heang-Ping Chan, Lubomir M. Hadjiiski, Marilyn A. Roubidoux, Mark A. Helvie M.D., Jun Ge, Chuan Zhou, Yi-Ta Wu

Author Affiliations +

Proceedings Volume 6514, Medical Imaging 2007: Computer-Aided Diagnosis; 651405 (2007) https://doi.org/10.1117/12.713768
Event: Medical Imaging, 2007, San Diego, CA, United States

Abstract

An important purpose of a CAD system is that it can serve as a second reader to alert radiologists to subtle cancers that may be overlooked. In this study, we are developing new computer vision techniques to improve the detection performance for subtle masses on prior mammograms. A data set of 159 patients containing 318 current mammograms and 402 prior mammograms was collected. A new technique combining gradient field analysis with Hessian analysis was developed to prescreen for mass candidates. A suspicious structure in each identified location was initially segmented by seed-based region growing and then refined by using an active contour method. Morphological, gray level histogram and run-length statistics features were extracted. Rule-based and LDA classifiers were trained to differentiate masses from normal tissues. We randomly divided the data set into two independent sets; one set of 78 cases for training and the other set of 81 cases for testing. With our previous CAD system, the case-based sensitivities on prior mammograms were 63%, 48% and 32% at 2, 1 and 0.5 FPs/image, respectively. With the new CAD system, the case-based sensitivities were improved to 74%, 56% and 35%, respectively, at the same FP rates. The difference in the FROC curves was statistically significant (p<0.05 by AFROC analysis). The performances of the two systems for detection of masses on current mammograms were comparable. The results indicated that the new CAD system can improve the detection performance for subtle masses without a trade-off in detection of average masses.

Citation Download Citation

Jun Wei, Berkman Sahiner, Heang-Ping Chan, Lubomir M. Hadjiiski, Marilyn A. Roubidoux, Mark A. Helvie M.D., Jun Ge, Chuan Zhou, and Yi-Ta Wu "Computer-aided detection of breast masses on prior mammograms", Proc. SPIE 6514, Medical Imaging 2007: Computer-Aided Diagnosis, 651405 (29 March 2007); https://doi.org/10.1117/12.713768

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

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
7 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Mammography

CAD systems

Computer aided design

Statistical analysis

Cancer

Computer aided diagnosis and therapy

Visibility

Show All Keywords

Keywords/Phrases

Search In:

Publication Years