Jiewei Jiang, Haiyang Liu, Lang He, Mengjie Pei, Tongtong Lin, Hailong Yang, Junhua Yang, Jiamin Gong, Xumeng Wei, Mingmin Zhu, Guohai Wu, Zhongwen Li
BACKGROUND: The accurate detection of eyelid tumors is essential for effective treatment, but it can be challenging due to small and unevenly distributed lesions surrounded by irrelevant noise. Moreover, early symptoms of eyelid tumors are atypical, and some categories of eyelid tumors exhibit similar color and texture features, making it difficult to distinguish between benign and malignant eyelid tumors, particularly for ophthalmologists with limited clinical experience. METHODS: We propose a hybrid model, HM_ADET, for automatic detection of eyelid tumors, including YOLOv7_CNFG to locate eyelid tumors and vision transformer (ViT) to classify benign and malignant eyelid tumors...
February 28, 2024: Biomedical Engineering Online