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Early stage detection of breast cancer using novel image processing techniques, Matlab and Labview implementation
- Source :
- 2013 15th International Conference on Advanced Computing Technologies (ICACT).
- Publication Year :
- 2013
- Publisher :
- IEEE, 2013.
-
Abstract
- Early detection of breast cancer is carried out by using mammographic images. Due to low contrast nature of these images, it is difficult to detect signs such as micro calcifications and masses. This paper describes novel algorithms for early detection of breast cancer using image processing techniques. Novel algorithms are implemented for 1) Mass region extraction to get exact shape of the mass 2) Superposition of boundary of mass on mammogram helps doctors to view the boundary easily as mass region overlaps with breast parenchyma 3) Extraction of texture features like mean, standard deviation, entropy, kurtosis etc, geometric features like area perimeter L:S, ENC, (Elliptical normalized circumference) wavelet based features, so that signatures can be assigned for identification and classification of benign and malignant masses. Fourteen patients' mammograms have been processed. Features of six patients have been extracted that have masses.
- Subjects :
- Contextual image classification
medicine.diagnostic_test
business.industry
Computer science
Feature extraction
Wavelet transform
Cancer
Image processing
Pattern recognition
Breast parenchyma
medicine.disease
Breast cancer
Wavelet
Image texture
medicine
Mammography
Computer vision
Artificial intelligence
business
Subjects
Details
- Database :
- OpenAIRE
- Journal :
- 2013 15th International Conference on Advanced Computing Technologies (ICACT)
- Accession number :
- edsair.doi...........0e2d46ea19b843aa41d954872c1c1118