Literature DB >> 19921335

Automatic detection of microaneurysms and hemorrhages in digital fundus images.

Giri Babu Kande1, T Satya Savithri, P Venkata Subbaiah.   

Abstract

An efficient approach for automatic detection of red lesions in ocular fundus images based on pixel classification and mathematical morphology is proposed. Experimental evaluation of the proposed approach demonstrates better performance over other red lesion detection algorithms, and when determining whether an image contains red lesions the proposed approach achieves a sensitivity of 100% and specificity of 91%.

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Year:  2009        PMID: 19921335      PMCID: PMC3046669          DOI: 10.1007/s10278-009-9246-0

Source DB:  PubMed          Journal:  J Digit Imaging        ISSN: 0897-1889            Impact factor:   4.056


  6 in total

1.  Locating the optic nerve in a retinal image using the fuzzy convergence of the blood vessels.

Authors:  Adam Hoover; Michael Goldbaum
Journal:  IEEE Trans Med Imaging       Date:  2003-08       Impact factor: 10.048

2.  Automatic detection of red lesions in digital color fundus photographs.

Authors:  Meindert Niemeijer; Bram van Ginneken; Joes Staal; Maria S A Suttorp-Schulten; Michael D Abràmoff
Journal:  IEEE Trans Med Imaging       Date:  2005-05       Impact factor: 10.048

3.  Detection of blood vessels in retinal images using two-dimensional matched filters.

Authors:  S Chaudhuri; S Chatterjee; N Katz; M Nelson; M Goldbaum
Journal:  IEEE Trans Med Imaging       Date:  1989       Impact factor: 10.048

4.  Automated microaneurysm detection using local contrast normalization and local vessel detection.

Authors:  Alan D Fleming; Sam Philip; Keith A Goatman; John A Olson; Peter F Sharp
Journal:  IEEE Trans Med Imaging       Date:  2006-09       Impact factor: 10.048

5.  An image-processing strategy for the segmentation and quantification of microaneurysms in fluorescein angiograms of the ocular fundus.

Authors:  T Spencer; J A Olson; K C McHardy; P F Sharp; J V Forrester
Journal:  Comput Biomed Res       Date:  1996-08

6.  Improvement of automated detection method of hemorrhages in fundus images.

Authors:  Yuji Hatanaka; Toshiaki Nakagawa; Yoshinori Hayashi; Takeshi Hara; Hiroshi Fujita
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2008
  6 in total
  3 in total

1.  A Novel Method for Correcting Non-uniform/Poor Illumination of Color Fundus Photographs.

Authors:  Sajib Kumar Saha; Di Xiao; Yogesan Kanagasingam
Journal:  J Digit Imaging       Date:  2018-08       Impact factor: 4.056

2.  Statistical Geometrical Features for Microaneurysm Detection.

Authors:  Arati Manjaramkar; Manesh Kokare
Journal:  J Digit Imaging       Date:  2018-04       Impact factor: 4.056

3.  An automated unsupervised deep learning-based approach for diabetic retinopathy detection.

Authors:  Huma Naz; Rahul Nijhawan; Neelu Jyothi Ahuja
Journal:  Med Biol Eng Comput       Date:  2022-10-24       Impact factor: 3.079

  3 in total

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