4 March 2015 SA-SVM based automated diagnostic system for skin cancer
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Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94432L (2015) https://doi.org/10.1117/12.2179094
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China
Abstract
Early diagnosis of skin cancer is one of the greatest challenges due to lack of experience of general practitioners (GPs). This paper presents a clinical decision support system aimed to save time and resources in the diagnostic process. Segmentation, feature extraction, pattern recognition, and lesion classification are the important steps in the proposed decision support system. The system analyses the images to extract the affected area using a novel proposed segmentation method H-FCM-LS. The underlying features which indicate the difference between melanoma and benign lesions are obtained through intensity, spatial/frequency and texture based methods. For classification purpose, self-advising SVM is adapted which showed improved classification rate as compared to standard SVM. The presented work also considers analyzed performance of linear and kernel based SVM on the specific skin lesion diagnostic problem and discussed corresponding findings. The best diagnostic rates obtained through the proposed method are around 90.5 %.
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Ammara Masood, Ammara Masood, Adel Al-Jumaily, Adel Al-Jumaily, } "SA-SVM based automated diagnostic system for skin cancer", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94432L (4 March 2015); doi: 10.1117/12.2179094; https://doi.org/10.1117/12.2179094
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