Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/17358
Title: Robust object extraction and change detection in retinal images for diabetic clinical studies
Authors: Li, Q
You, J 
Bhattacharya, P
Keywords: Blood vessels
Diseases
Eye
Feature extraction
Image classification
Image segmentation
Medical image processing
Object detection
Issue Date: 2007
Publisher: IEEE
Source: IEEE Symposium on Computational Intelligence in Image and Signal Processing, 2007 : CIISP 2007, 1-5 April 2007, Honolulu, HI, p. 357-362 How to cite?
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
URI: http://hdl.handle.net/10397/17358
ISBN: 1-4244-0707-9
DOI: 10.1109/CIISP.2007.369195
Appears in Collections:Conference Paper

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