Skin Lesion Detection Using Fuzzy Approach and Classification with CNN

Skin Lesion Detection Using Fuzzy Approach and Classification with CNN

Автор: Prashengit Dhar, Sunanda Guha

Журнал: International Journal of Engineering and Manufacturing @ijem

Статья в выпуске: 1 vol.11, 2021 года.

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Skin lesion detection at early stage is very effective for patients. As a result, patients can get time for treatment. Moreover, this early detection helps a patient in the long-time survival. However, skin lesion detection from a dermoscopic images is not a general task. Due to inter and intra-observer variations in human interpretations, research on skin lesion detection from dermoscopic images become important. In this paper, we proposed a method to segment and detect lesion of skin from images. The proposed method is based on a set of rules of fuzzy logic approach. Firstly, a set of rules is applied on dermoscopic images. The output is then thresholded. Closing operation as a morphological tool is used on the thresholded image. Then area filtering takes a place which results in the desired output. With respect to different learning models, CNN shows better performance in classifying ISIC and Dermis-dermquest dataset. The system delivers a significant performance, which is remarkable and comparable.

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Dermoscopic image, fuzzy logic, segmentation, lesion detection

Короткий адрес: https://sciup.org/15017333

IDR: 15017333   |   DOI: 10.5815/ijem.2021.01.02

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