Two-view information fusion for improvement of computer-aided detection (CAD) of breast masses on mammograms

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

doi:10.1117/12.654593

10 March 2006 Two-view information fusion for improvement of computer-aided detection (CAD) of breast masses on mammograms

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

Author Affiliations +

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 614424 (2006) https://doi.org/10.1117/12.654593
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

We are developing a two-view information fusion method to improve the performance of our CAD system for mass detection. Mass candidates on each mammogram were first detected with our single-view CAD system. Potential object pairs on the two-view mammograms were then identified by using the distance between the object and the nipple. Morphological features, Hessian feature, correlation coefficients between the two paired objects and texture features were used as input to train a similarity classifier that estimated a similarity scores for each pair. Finally, a linear discriminant analysis (LDA) classifier was used to fuse the score from the single-view CAD system and the similarity score. A data set of 475 patients containing 972 mammograms with 475 biopsy-proven masses was used to train and test the CAD system. All cases contained the CC view and the MLO or LM view. We randomly divided the data set into two independent sets of 243 cases and 232 cases. The training and testing were performed using the 2-fold cross validation method. The detection performance of the CAD system was assessed by free response receiver operating characteristic (FROC) analysis. The average test FROC curve was obtained from averaging the FP rates at the same sensitivity along the two corresponding test FROC curves from the 2-fold cross validation. At the case-based sensitivities of 90%, 85% and 80% on the test set, the single-view CAD system achieved an FP rate of 2.0, 1.5, and 1.2 FPs/image, respectively. With the two-view fusion system, the FP rates were reduced to 1.7, 1.3, and 1.0 FPs/image, respectively, at the corresponding sensitivities. The improvement was found to be statistically significant (p<0.05) by the AFROC method. Our results indicate that the two-view fusion scheme can improve the performance of mass detection on mammograms.

Citation Download Citation

Jun Wei, Berkman Sahiner, Lubomir M. Hadjiiski, Heang-Ping Chan, Mark A. Helvie M.D., Marilyn A. Roubidoux, Chuan Zhou, Jun Ge, and Yiheng Zhang "Two-view information fusion for improvement of computer-aided detection (CAD) of breast masses on mammograms", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 614424 (10 March 2006); https://doi.org/10.1117/12.654593

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