A survey on computer aided diagnosis for ocular diseases

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• 作者：Zhuo Zhang (6) (7)
  Ruchir Srivastava (6)
  Huiying Liu (6)
  Xiangyu Chen (6)
  Lixin Duan (6)
  Damon Wing Kee Wong (6)
  Chee Keong Kwoh (7)
  Tien Yin Wong (8)
  Jiang Liu (6)
  
  6. Institute for Infocomm Research ; 1 Fusionopolis Way ; Singapore ; Singapore
  7. Nanyang Technological University ; Nanyang Drive ; Singapore ; Singapore
  8. Singapore National Eye Centre ; Third Hospital Avenue ; Singapore ; Singapore
  
• 关键词：Computer Aided Diagnosis (CAD) ; Ocular diseases ; Review ; Clinical data ; Ocular imaging ; Genetic information
• 刊名：BMC Medical Informatics and Decision Making
• 出版年：2014
• 出版时间：December 2014
• 年：2014
• 卷：14
• 期：1
• 全文大小：3,601 KB
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• 刊物主题：Health Informatics; Information Systems and Communication Service; Management of Computing and Information Systems;
• 出版者：BioMed Central
• ISSN：1472-6947

文摘

Background Computer Aided Diagnosis (CAD), which can automate the detection process for ocular diseases, has attracted extensive attention from clinicians and researchers alike. It not only alleviates the burden on the clinicians by providing objective opinion with valuable insights, but also offers early detection and easy access for patients. Method We review ocular CAD methodologies for various data types. For each data type, we investigate the databases and the algorithms to detect different ocular diseases. Their advantages and shortcomings are analyzed and discussed. Result We have studied three types of data (i.e., clinical, genetic and imaging) that have been commonly used in existing methods for CAD. The recent developments in methods used in CAD of ocular diseases (such as Diabetic Retinopathy, Glaucoma, Age-related Macular Degeneration and Pathological Myopia) are investigated and summarized comprehensively. Conclusion While CAD for ocular diseases has shown considerable progress over the past years, the clinical importance of fully automatic CAD systems which are able to embed clinical knowledge and integrate heterogeneous data sources still show great potential for future breakthrough.