Back to articles
Articles
Volume: 28 | Article ID: art00004
Image
Automatic Mobile Retinal Microaneurysm Detection Using Handheld Fundus Camera via Cloud Computing
  DOI :  10.2352/ISSN.2470-1173.2016.11.IMAWM-469  Published OnlineFebruary 2016
Abstract

This paper presents a new system to monitor retinal microaneurysm which are regarded as the first sign of diabetic retinopathy(DR). The proposed approach to automatic microaneurysm detection aims to enhance screening large populations. Most of the existing computer-aided systems for microaneurysm detection are based on the sophisticated medical device in a clinical environment. However, the popular medical devices such as table fundus camera and portable fundus camera are subject to certain limitations for its usage beyond the scope of clinical practice. The challenges include the complexity of operation, cost issue and requirement of professional maintenance, etc. Unlike the conventional approaches, we developed an automatic mobile retinal microaneurysm detection system by using a handheld fundus camera to facilitate retinal healthcare and monitoring with flexibility and convenience. Our system includes: (1) retinal image capturing by handheld fundus camera;(2) retinal image analysis via cloud computing;(3) microaneurysm detection by Multi-orientation Sum of Matched Filter and SVM. The experimental results demonstrate the feasibility of our system by performance improvement on the aspects of speed, accuracy, and convenience.

Subject Areas :
Views 7
Downloads 1
 articleview.views 7
 articleview.downloads 1
  Cite this article 

Jane YOU, Qin LI, Zhenhua GUO, "Automatic Mobile Retinal Microaneurysm Detection Using Handheld Fundus Camera via Cloud Computingin Proc. IS&T Int’l. Symp. on Electronic Imaging: Imaging and Multimedia Analytics in a Web and Mobile World,  2016,  https://doi.org/10.2352/ISSN.2470-1173.2016.11.IMAWM-469

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2016
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology
7003 Kilworth Lane, Springfield, VA 22151 USA