Robust object extraction and change detection in retinal images for diabetic clinical studies

Qin Li, Jia You, Lei Zhang, Prabir Bhattacharya

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

With the rapid advances in computing and electronic imaging technology, there has been increasing interest in developing computer aided medical diagnosis systems to improve the medical service for the public. Images of ocular fundus provide crucial observable features for diagnosing many kinds of pathologies such as diabetes, hypertension, and arteriosclerosis. A computer-aided retinal image analysis system can help eye specialists to screen larger populations and produce better evaluation of treatment and more effective clinical study. This paper is focused on the immediate needs for clinical studies on diabetic patients. Our system includes multiple feature extraction, robust retinal vessel segmentation, hierarchical change detection and classification. The output throughout this system will assist doctors to speed up screening large populations for abnormal cases, and facilitate evaluation of treatment for clinical study.
Original languageEnglish
Title of host publicationProceedings of the 2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing, CIISP 2007
Pages357-362
Number of pages6
DOIs
Publication statusPublished - 25 Sep 2007
Event2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing, CIISP 2007 - Honolulu, HI, United States
Duration: 1 Apr 20075 Apr 2007

Conference

Conference2007 IEEE Symposium on Computational Intelligence in Image and Signal Processing, CIISP 2007
Country/TerritoryUnited States
CityHonolulu, HI
Period1/04/075/04/07

ASJC Scopus subject areas

  • Artificial Intelligence
  • Signal Processing
  • Software
  • Electrical and Electronic Engineering

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