NDLI: Retinal vessel segmentation approach based on corrected morphological transformation and fractal dimension

Content Provider	IET Digital Library
Author	Wang, Weihua Wang, Weiqing Hu, Zhangping
Abstract	The morphological structure of retinal vessels plays an important role in analysing and diagnosing fundus disease. In this study, an unsupervised automatic segmentation method for retinal blood vessels with corrected morphological transformation and fractal dimension is proposed. To enhance the contrast between retinal vessels and background in a fundus image, the morphological operator with linear structural elements is used; to remove the lesion and its light reflection, a compensation method is proposed; to extract the objects from a grey image, the multi-threshold approach is applied; to recognise the blood vessels and noise from the fundus image, a new method based on fractal dimension is presented. The new approach is tested in detail on three public databases STARE, DRIVE and HRF. Experimental results show that the segmentation algorithm is better than other existing unsupervised automatic segmentation algorithms, and the new approach is robust.
Starting Page	2538
Ending Page	2547
Page Count	10
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 13, Nov (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/13
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5636
Journal	IET Image Processing
Publisher Date	2019-08-22
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Anatomy And Optics of The Eye Biology And Medical Computing Biomedical Imaging/measurement Biomedical Optical Imaging Blood Vessels Compensation Method Computer Vision And Image Processing Technique Diseases Eye Fractal Dimension Fundus Disease Fundus Image Grey Image Image Segmentation Linear Structural Element Medical Image Processing Morphological Structure Morphological Transformation Multithreshold Approach Optical And Laser Radiation Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Retinal Vessel Segmentation Approach Unsupervised Automatic Segmentation Algorithm
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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