AI-enabled support system for melanoma detection and Classification

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作者
Saxena, Vivek Sen [1 ]
Johri, Prashant [1 ]
Kumar, Avneesh [1 ]
机构
[1] Galgotias University, India
关键词
Dermatology - Learning algorithms - Support vector machines - Feature extraction - Image classification - Oncology;
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摘要
Skin lesion melanoma is the deadliest type of cancer. Artificial intelligence provides the power to classify skin lesions as melanoma and non-melanoma. The proposed system for melanoma detection and classification involves four steps: pre-processing, resizing all the images, removing noise and hair from dermoscopic images; image segmentation, identifying the lesion area; feature extraction, extracting features from segmented lesion and classification; and categorizing lesion as malignant (melanoma) and benign (non-melanoma). Modified GrabCut algorithm is employed to generate skin lesion. Segmented lesions are classified using machine learning algorithms such as SVM, k-NN, ANN, and logistic regression and evaluated on performance metrics like accuracy, sensitivity, and specificity. Results are compared with existing systems and achieved higher similarity index and accuracy. Copyright © 2021, IGI Global. Copying or distributing in print or electronic forms without written permission of IGI Global is prohibited.
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页码:72 / 93
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