Review of Deep Learning Based Segmentation and Recognition of Dermatological Images

Abstract

Dermatosis are prevalent across different age groups, and using deep learning methods to assist general practitioners can improve the accuracy of their diagnoses. This paper summarizes the applications of deep learning in the field of image processing, particularly in the segmentation and classification of skin disease images. First, it introduces the main deep learning models used in image segmentation and classification. Then, it provides a detailed overview of the specific applications and improvements of various segmentation and classification models in the task of skin disease image processing. By summarizing relevant studies, it demonstrates the significant advancements in accuracy achieved by deep learning in skin disease image processing. Finally, the paper concludes with a summary and offers prospects for the future of intelligent skin disease diagnosis.