Detection of microaneurysms using multi-scale correlation coefficients

Bob Zhang, Xiangqian Wu, Jia You, Qin Li, Fakhri Karray

Research output: Journal article publicationJournal articleAcademic researchpeer-review

161 Citations (Scopus)

Abstract

This paper presents a new approach to the computer aided diagnosis (CAD) of diabetic retinopathy (DR)-a common and severe complication of long-term diabetes which damages the retina and cause blindness. Since microaneurysms are regarded as the first signs of DR, there has been extensive research on effective detection and localization of these abnormalities in retinal images. In contrast to existing algorithms, a new approach based on multi-scale correlation filtering (MSCF) and dynamic thresholding is developed. This consists of two levels, microaneurysm candidate detection (coarse level) and true microaneurysm classification (fine level). The approach was evaluated based on two public datasets-ROC (retinopathy on-line challenge, http://roc.healthcare.uiowa.edu) and DIARETDB1 (standard diabetic retinopathy database, http://www.it.lut.fi/project/imageret/diaretdb1). We conclude our method to be effective and efficient.
Original languageEnglish
Pages (from-to)2237-2248
Number of pages12
JournalPattern Recognition
Volume43
Issue number6
DOIs
Publication statusPublished - 1 Jun 2010

Keywords

  • Computer-aided diagnosis (CAD)
  • Diabetic retinopathy (DR)
  • Microaneurysm (red lesion) detection
  • Multi-scale correlation filtering

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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