深度学习在圆锥角膜早期诊断辅助系统中的应用实践
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  • 英文篇名:Application of Deep Learning in Early Diagnosis Assistant System of Keratoconus
  • 作者:谭安祖 ; 余曼 ; 陈宣 ; 胡亮
  • 英文作者:TAN Anzu;YU Man;CHEN Xuan;HU Liang;The Eye Hospital of Wenzhou Medical University;
  • 关键词:圆锥角膜 ; 光学相干断层扫描技术 ; 深度学习
  • 英文关键词:keratoconus;;optical coherence tomography technique;;deep learning
  • 中文刊名:ZYLZ
  • 英文刊名:Chinese Journal of Medical Instrumentation
  • 机构:温州医科大学附属眼视光医院;
  • 出版日期:2019-03-30
  • 出版单位:中国医疗器械杂志
  • 年:2019
  • 期:v.43
  • 基金:浙江省自然科学基金(Y17H120030)
  • 语种:中文;
  • 页:ZYLZ201902002
  • 页数:3
  • CN:02
  • ISSN:31-1319/R
  • 分类号:8-10
摘要
针对圆锥角膜早期病变尚未存在标准诊断的问题,同时为了辅助特检科医师、眼科医师有效地进行早期诊断,通过分析各检测仪器的优缺点,选择在角膜OCT检查上应用深度学习技术,构建圆锥角膜早期诊断辅助系统。该系统采用改良后的VGG-16实现了约68%圆锥角膜病变的识别精度,临床验证该系统能在一定程度上辅助医师下达诊断的信心,同时医师对OCT检查的再标记可以帮助系统训练出更精准的判断。
        In view of the problem that there is no standard diagnosis for early stage keratoconus disease,at the same time to assist the special examiner and ophthalmologist to make the early diagnosis effectively, the advantages and disadvantages of each testing instrument were analyzed. In order to construct an assistant system for early diagnosis of keratoconus, a deep learning technique was applied in corneal OCT examination. The system used improved VGG-16 to realize the recognition accuracy of about 68% keratoconus keratopathy, and the clinical results showed that the system can help doctors to give diagnosis confidence to a certain extent. At the same time, the physician's re-marking of OCT can help train the system for more accurate judgment.
引文
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