AI-Enabled Support System for Melanoma Detection and Classification
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...
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Published in | International journal of reliable and quality e-healthcare Vol. 10; no. 4; pp. 58 - 75 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Hershey
IGI Global
01.10.2021
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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ISSN: | 2160-9551 2160-956X |
DOI: | 10.4018/IJRQEH.2021100104 |