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author:

Zheng, S.-H. (Zheng, S.-H..) [1] | Chen, J. (Chen, J..) [2] | Pan, L. (Pan, L..) [3] | Guo, J. (Guo, J..) [4] | Yu, L. (Yu, L..) [5]

Indexed by:

Scopus PKU CSCD

Abstract:

In automatic retinal image analysis, the location of the optic disk and macula fovea is the prerequisite for a system of computer aided diagnosis or automatic screening of diabetic retinopathy. This paper proposes a novel method to detect macular firstly before optic disk location or vessels detection using directional local contrast filter and local vessel density feature, which improves effectively the accuracy of the detection of the macular and optic disk, and is different from existing algorithms that detected optic disk firstly before macula fovea location. 169 color images with diabetic macular edema from HEI-MED public database are used to evaluate the performance of the developed method. From the experimental results, the accuracy rate both of macular and optic disk detection is found to be 98.2%. The proposed method is simple and unsupervised, and has high practical value. ©, 2014, Science Press. All right reserved.

Keyword:

Directional local contrast; Macula fovea; Optic disk; Pattern recognition; Retinal image; Vessel Segmentation

Community:

  • [ 1 ] [Zheng, S.-H.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 2 ] [Chen, J.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 3 ] [Pan, L.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, 350108, China
  • [ 4 ] [Guo, J.]Eye Center of the First Affiliated Hospital of Fujian Medical University, Fuzhou, 350005, China
  • [ 5 ] [Yu, L.]College of Physics and Information Engineering, Fuzhou University, Fuzhou, 350108, China

Reprint 's Address:

  • [Zheng, S.-H.]College of Physics and Information Engineering, Fuzhou UniversityChina

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Source :

Journal of Electronics and Information Technology

ISSN: 1009-5896

CN: 11-4494/TN

Year: 2014

Issue: 11

Volume: 36

Page: 2586-2592

0 . 5 0 0

JCR@2023

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 10

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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