Programs
- M. Tech. in Automotive Engineering -
- Fellowship In Interventional Pulmonology and Pulmonary Critical care - Fellowship
Publication Type : Journal Article
Publisher : Journal of Cybernetics and Information Technologies
Source : Journal of Cybernetics and Information Technologies (2012)
Url : https://cit.iict.bas.bg/CIT_2012/v12-2/Don,Chung,Revathy,Choi,Min-pp-69-83.pdf
Campus : Amritapuri
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2012
Abstract : Accurate classification of images is essential for the analysis of mammograms in computer aided diagnosis of breast cancer. We propose a new approach to classify mammogram images based on fractal features. Given a mammogram image, we first eliminate all the artifacts and extract the salient features such as Fractal Dimension (FD) and Fractal Signature (FS). These features provide good descriptive values of the region. Second, a trainable multilayer feed forward neural network has been designed for the classification purposes and we compared the classification test results with K-Means. The result reveals that the proposed approach can classify with a good performance rate of 98%.
Cite this Research Publication : Dr. Don S. and Dugki Min, “A New Approach for Mammogram Image Classification Using Fractal Properties”, Journal of Cybernetics and Information Technologies, 2012.