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- Title
WAVELET FEATURE AND SVM FOR DETECTION AND CLASSIFICATION OF MICROCALCIFICATIONS.
- Authors
JHANSI, J.; KALPANA, M.; SHOBHA, M.
- Abstract
The objective of this paper is to detect the microcalcifications from the digitized mammograms using support vector machine, based on effective wavelet feature analysis. Microcalcifications are tiny deposits of calcium in the breast tissue which are potential indicators for early detection of breast cancer. The identification of cancer tissue is prohibited by the poor contrast level of mammograms. In this paper, new approach helps to identify cancer tissue with better accuracy. Microcalcifications are extracted by using wavelet based feature extraction and compared with other feature extraction like Gabor filter based extraction. The results from the feature extraction are classified using support vector machine classifier that provides better performance than other classifiers on wavelet based feature extraction.
- Subjects
MAMMOGRAMS; BREAST cancer diagnosis; CALCIFICATIONS of the breast; SUPPORT vector machines; CLASSIFICATION algorithms
- Publication
I-Manager's Journal on Digital Signal Processing, 2017, Vol 5, Issue 1, p7
- ISSN
2321-7480
- Publication type
Article
- DOI
10.26634/jdp.5.1.13526