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AI-Enabled Support System for Melanoma Detection and Classification

Author

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  • Vivek Sen Saxena

    (Galgotias University, India)

  • Prashant Johri

    (Galgotias University, India)

  • Avneesh Kumar

    (Galgotias University, India)

Abstract

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.

Suggested Citation

  • Vivek Sen Saxena & Prashant Johri & Avneesh Kumar, 2021. "AI-Enabled Support System for Melanoma Detection and Classification," International Journal of Reliable and Quality E-Healthcare (IJRQEH), IGI Global, vol. 10(4), pages 58-75, October.
    • Handle: RePEc:igg:jrqeh0:v:10:y:2021:i:4:p:58-75
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