Paper
24 March 2016 Improvement of retinal blood vessel detection by spur removal and Gaussian matched filtering compensation
Di Xiao, Janardhan Vignarajan, Dong An, Mei-Ling Tay-Kearney, Yogi Kanagasingam
Author Affiliations +
Abstract
Retinal photography is a non-invasive and well-accepted clinical diagnosis of ocular diseases. Qualitative and quantitative assessment of retinal images is crucial in ocular diseases related clinical application. In this paper, we proposed approaches for improving the quality of blood vessel detection based on our initial blood vessel detection methods. A blood vessel spur pruning method has been developed for removing the blood vessel spurs both on vessel medial lines and binary vessel masks, which are caused by artifacts and side-effect of Gaussian matched vessel enhancement. A Gaussian matched filtering compensation method has been developed for removing incorrect vessel branches in the areas of low illumination. The proposed approaches were applied and tested on the color fundus images from one publicly available database and our diabetic retinopathy screening dataset. A preliminary result has demonstrated the robustness and good performance of the proposed approaches and their potential application for improving retinal blood vessel detection.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Di Xiao, Janardhan Vignarajan, Dong An, Mei-Ling Tay-Kearney, and Yogi Kanagasingam "Improvement of retinal blood vessel detection by spur removal and Gaussian matched filtering compensation", Proc. SPIE 9785, Medical Imaging 2016: Computer-Aided Diagnosis, 97852E (24 March 2016); https://doi.org/10.1117/12.2216799
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Cited by 1 scholarly publication.
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KEYWORDS
Blood vessels

Blood

Electroluminescence

Image segmentation

Binary data

Image enhancement

Image processing

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