Technical Name 基於轉移學習之青光眼眼底照片診斷系統-適於各醫療院所之平台發展
Project Operator Taipei Veterans General Hospital
Project Host 1 劉瑞玲 2 盧鴻興 (總主持人:張德明)
Summary A transfer learning-assisted glaucoma detection system was build first with training images from the fundus images database of Taipei Veterans General Hospital,then fine-tuned to improve its applicability on fundus images from different datasets. This system aims to assist clinic-based glaucoma screening to increase the diagnostic rate of glaucoma by using existing healthcare facility.
Scientific Breakthrough Glaucoma is the leading cause of irreversible blindness, but is underdiagnosed worldwide. The diagnosis of glaucoma is further complicated by inter-physician discordance, especially in the interpretation of fundus photographs. A transfer learning-assisted glaucoma detection system with a diagnostic accuracy of 90 may facilitate clinic-based glaucoma screening.
Industrial Applicability For each fundus image, this system provides a probability value representing the likelihoods of glaucoma as a reference for clinician. Clinician may arrange further evaluation for eyes at risk of glaucoma. This approach has great potential to identify glaucoma at an early stage in a cost-effective way to reduce the socioeconomic burden of glaucoma blindness.
Keyword Deep learning glaucoma diagnosis fundus photograph optic nerve blindness transfer learning
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  • 柯玉潔