Intelligent Medical Image Processing System Using Zero-shot Learning
DOI:
https://doi.org/10.18372/1990-5548.82.19373Keywords:
malignant skin tumors, artificial intelligence, intelligent diagnostics, dermatoscopic images, pre-processing, hybrid approachAbstract
The work is devoted to the intelligent diagnosis of malignant skin tumors. The classification of malignant skin tumors is presented. The greatest attention was paid to skin melanoma. The modern signs of melanoma were analyzed: Asymmetry, Boundary, Color, and Diameter, and additionally for nodular melanoma: Elevated, Firm, and Growing. A review of works on using artificial intelligence to diagnose malignant skin tumors was performed. A methodology for the intelligent diagnosis of malignant skin tumors was proposed, which is based on the use of preprocessing of dermatoscopic images and solving the segmentation problem based on the use of a hybrid approach, which includes the use of a Segment Anything model based on the combination of the Zero-shot learning model, which consists of an image encoder, prompt encoder, lightweight mask decoder, with YOLOv11. ISIC 2018 was used as the dataset.
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