Intelligent Medical Image Processing System Using Zero-shot Learning
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Date
2024
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State University "Kyiv Aviation Institute"
Abstract
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.
Роботу присвячено інтелектуальній діагностиці злоякісних пухлин шкіри. Представлено класифікацію злоякісних пухлин шкіри. Найбільшу увагу було приділено меланомі шкіри. Проаналізовано сучасні ознаки меланоми: Asymmetry, Boundary, Color, Diameter та додатково для вузлової меланоми: Elevated, Firm, Growing . Виконано огляд робіт з використання штучного інтелекту у діагностиці злоякісних пухлин шкіри. Запропоновано методологію інтелектуальної діагностики злоякісних пухлин шкіри, яка базується на використанні попередньої обробки дерматоскопічних зображень та розв’язанні задачі сегментації на основі використання гібридного підходу, який включає застосування Segment Anything model на основі об’єднання моделі Zero-shot learning, яка складається з image encoder, prompt encoder, lightweight mask decoder з YOLOv11.В якості датасету було використано ISIC 2018.
Description
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Keywords
malignant skin tumors, artificial intelligence, intelligent diagnostics, dermatoscopic images, preprocessing, hybrid approach, злоякісні пухлини шкіри, штучний інтелект, інтелектуальна діагностика, дерматоскопічні зображення, попередня обробка, гібридний підхід
Citation
Sineglazov V. M. Intelligent Medical Image Processing System Using Zero-shot Learning / V. M. Sineglazov, O. O. Reshetnik // Electronics and Control Systems, No 4(82) – Kyiv: ТОВ “Альянт”, 2024. –pp. 23–28