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An Intelligent Decision Support System for Retinal Disease Diagnosis based on SVM using a Smartphone

스마트폰을 이용한 SVM 기반 망막 질병 진단을 위한 지능적인 의사 결정 지원 시스템

  • Lee, Byung-Kwan (Department of Regional Economics, Kangwon National University) ;
  • Jeong, Eun-Hee (Department of Regional Economics, Kangwon National University) ;
  • Tifani, Yusrina (Department of Regional Economics, Kangwon National University)
  • Received : 2015.09.11
  • Accepted : 2015.09.25
  • Published : 2015.10.30

Abstract

This paper proposes a decision support system to recognizing retinal diseases. This paper uses a smartphone platform and cloud computing as the base of the system. A microscopic lens is attached int' the smartphone camera to capture the user retinal image for recognizing the user's retinal condition. An application is assembled in computer and then installed in to the smartphone. The application role is to connect between the system in smartphone and system in cloud, the application will send the retinal image to the cloud system to be classified. The paper uses OCFE (optimized classifier based on feature elimination) algorithm as the classifier. The retinal image is trained using combination of two ophthalmology databases DIARETDB1 v2.1 and STARE. Therefore, this system average accuracy is 88%, while the average error rate is 12%.

이 논문은 망막 질병을 인지하기 위한 의사결정 지원 시스템을 제안한다. 이 논문은 시스템의 기초로써 스마트 폰 플랫폼과 클라우드 컴퓨팅을 사용한다. 마이크로 렌즈는 사용자의 망막 상태를 인지하기 위해 사용자 망막 이미지를 캡쳐 할 수 있도록 스마트 폰 카메라에 부착되어 있다. 어플리케이션은 컴퓨터에서 생성된 후에 스마트 폰에 설치된다. 이 어플리케이션의 역할은 스마트 폰에 있는 시스템과 클라우드에 있는 시스템 사이를 연결시키는 것으로, 어플리케이션은 분류하기 위해 클라우드 시스템에 망막 이미지를 전송하는 것이다. 이 논문은 분류기로써 OCFE 알고리즘을 사용한다. 망막 이미지는 두 개의 안과학 데이터베이스 DIARETDB1 v2.1과 STARE의 조합을 사용하여 실험하였다. 그리하여 평균 에러율을 12%인 반면에, 이 시스템 평균 정확도는 88%로 나타났다.

Keywords

References

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