Breast tumor detection in double views mammography based on Simple Bias

Breast tumor detection is a most effective way to immunized against mammary cancer. It is known that the sort algorithm of extreme learning machine(ELM), in view of the feature model for breast X-ray image, is being applied in the computer aided detection of breast masses. On the basis of all these,...

Full description

Saved in:
Bibliographic Details
Published in2013 IEEE International Conference on Medical Imaging Physics and Engineering pp. 240 - 244
Main Authors Zhang, Shiya, Chen, Zhongzhou, Gu, Sheng, Qiu, Xihe, Qu, Qixun, Wang, Zhiqiong
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2013
Subjects
Accuracy
Breast tumors
double views
Extreme learning machine
Feature extraction
mammography
Simple Bias
Testing
Training
tumor detection
Online AccessGet full text

Cover

More Information
Summary:Breast tumor detection is a most effective way to immunized against mammary cancer. It is known that the sort algorithm of extreme learning machine(ELM), in view of the feature model for breast X-ray image, is being applied in the computer aided detection of breast masses. On the basis of all these, it is raised in this paper that marking for the suspicious region in the double view mammography by the use of ELM, then classifying the result of double views marking by using the Simple Bias classifier and finally gaining the detection result. The experiment with 444 cases or 222 pair of X-ray mammography from Liao Ning Province Cancer Hospital shows that, the breast tumor detection in double views mammography based on Simple Bias is an available and effective way to detect breast tumor.
DOI:10.1109/ICMIPE.2013.6864543