By Topic

Computerized Classification of Breast Tumors with Morphologic and Texture Features of Ultrasonic Images

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Yuanyuan Wang ; Dept. of Electron. Eng., Fudan Univ., Shanghai ; Jialin Shen ; Yi Guo ; Weiqi Wang

A computerized classification based on morphologic and texture features is proposed to increase the accuracy of the ultrasonic diagnosis of breast tumors. Firstly, tumor boundaries are obtained with the gray-level threshold segmentation algorithm and the dynamic programming method. Then five morphologic features and two texture features are extracted. Finally, an artificial neural network with the error back propagation algorithm is applied to classify breast tumors as benign or malignant. Experiments on 168 cases show that the proposed system yields the high accuracy, sensitivity and specificity. Therefore, it is concluded that this system performs well in the ultrasonic classification of breast tumors.

Published in:

Computer-Based Medical Systems, 2008. CBMS '08. 21st IEEE International Symposium on

Date of Conference:

17-19 June 2008