Noninvasive identification of Benign and malignant eyelid tumors using clinical images via deep learning system

Noninvasive identification of Benign and malignant eyelid tumors using clinical images via deep learning system

Abstract Eyelid tumors accounts for 5–10% of skin tumors. It is important but difficult to identify malignant eyelid tumors from benign lesions in a cost-effective way. Traditional screening methods for malignancy in eyelid tumors require laborious and time-consuming histopathological process. There...

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Bibliographic Details
Main Authors: Shiqi Hui, Li Dong, Kai Zhang, Zihan Nie, Xue Jiang, Heyan Li, Zhijia Hou, Jingwen Ding, Yue Wang, Dongmei Li
Format: Article
Language:English
Published: SpringerOpen 2022-06-01
Series:Journal of Big Data
Subjects:
Deep learning
Eyelid tumor
Clinical image
Online Access:https://doi.org/10.1186/s40537-022-00634-y

Internet

https://doi.org/10.1186/s40537-022-00634-y

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