Version 1
: Received: 21 June 2018 / Approved: 21 June 2018 / Online: 21 June 2018 (15:46:03 CEST)
How to cite:
Singh, M.; Singh, D.; Sharma, V. Breast tumor detection and classification in Mammograms: Gabor wavelet vs. statistical features. Preprints2018, 2018060343. https://doi.org/10.20944/preprints201806.0343.v1
Singh, M.; Singh, D.; Sharma, V. Breast tumor detection and classification in Mammograms: Gabor wavelet vs. statistical features. Preprints 2018, 2018060343. https://doi.org/10.20944/preprints201806.0343.v1
Singh, M.; Singh, D.; Sharma, V. Breast tumor detection and classification in Mammograms: Gabor wavelet vs. statistical features. Preprints2018, 2018060343. https://doi.org/10.20944/preprints201806.0343.v1
APA Style
Singh, M., Singh, D., & Sharma, V. (2018). Breast tumor detection and classification in Mammograms: Gabor wavelet vs. statistical features. Preprints. https://doi.org/10.20944/preprints201806.0343.v1
Chicago/Turabian Style
Singh, M., Dharmesh Singh and Vipul Sharma. 2018 "Breast tumor detection and classification in Mammograms: Gabor wavelet vs. statistical features" Preprints. https://doi.org/10.20944/preprints201806.0343.v1
Abstract
Breast cancer is the second cause of fatality among all cancers for women. Automatic classification of breast cancer lesions in mammograms is a challenging task due to the irregularity and complexity of the location, size, shape, and texture of these lesions. The intensity dissimilarity has been found between breast cancer tissues and normal tissues, when a multi-spectral anatomical mammographic screening scans have been done. In this work, two approaches have been evaluated to classify the breast tumor lesions. The first one is through Gabor wavelet features and the second one is Statistical features. Subsequently, support vector machine, Multilayer Perceptron and KNN classifiers have been used with computer based method for breast tumor classification.
Medicine and Pharmacology, Oncology and Oncogenics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
