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Post-processing for retinal vessel detection
Author(s): Xiaohong Wang; Xudong Jiang
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Paper Abstract

Retinal vessel extraction plays a vital role in the computer-aided analysis of ophthalmology diseases. In this paper, we propose a new post-processing method to enhance retinal vessel classification performance. This proposed method automatically connects the discontinuous thin vessel fragments and smooth the thick vessel edges by the combination of two mathematical morphological operations, skeleton and erosion. Moreover, the proposed method removes the pathological regions by comparing the geometric structures of vessels and pathological regions. Experimental results demonstrate that the proposed method performs well for retinal vessel classification enhancement, i.e. maintain the integrity of vessel trees and reduce the false detection of pathological regions, making the vessel classification results better than those presented by the state-of-the-art approaches in comparison.

Paper Details

Date Published: 9 August 2018
PDF: 5 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 1080656 (9 August 2018); doi: 10.1117/12.2502813
Show Author Affiliations
Xiaohong Wang, Nanyang Technological Univ. (Singapore)
Xudong Jiang, Nanyang Technological Univ. (Singapore)


Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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