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Authors
Affiliations
1 Karpagam University, Coimbatore, Tamil Nadu, IN
2 Indra Ganesan College of Engineering, Trichy, Tamil Nadu, IN
Source
Digital Image Processing, Vol 5, No 11 (2013), Pagination: 483-487
Abstract
Mammogram is measured the most consistent method for early detection of breast cancer. Computer-aided diagnosis system is also able to support radiologist to detect abnormalities earlier and more rapidly. In this paper the performance evaluation of the computer aided diagnostic system for the classification of microcalcification in digital mammogram based on Discrete Wavelet Transform (DWT), Stochastic Neighbor Embedding (SNE) and the Support Vector Machine (SVM) is presented. This proposed system classifies the mammogram images into normal or abnormal, and the abnormal severity into benign or malignant. Mammography Image Analysis society (MIAS) database is used to evaluate the proposed system. The average classification rate achieved is very satisfied.
Keywords
Discrete Wavelet Transform, Stochastic Neighbor Embedding, Digital Mammograms, Microcalcification.
