Fast vessel segmentation in retinal images using multi-scale enhancement and second-order local entropy

H. Yu; S. Barriga; C. Agurto; G. Zamora; W. Bauman; P. Soliz

doi:10.1117/12.911547

23 February 2012 Fast vessel segmentation in retinal images using multi-scale enhancement and second-order local entropy

H. Yu; S. Barriga; C. Agurto; G. Zamora; W. Bauman; P. Soliz

Author Affiliations +

Proceedings Volume 8315, Medical Imaging 2012: Computer-Aided Diagnosis; 83151B (2012) https://doi.org/10.1117/12.911547
Event: SPIE Medical Imaging, 2012, San Diego, California, United States

Abstract

Retinal vasculature is one of the most important anatomical structures in digital retinal photographs. Accurate segmentation of retinal blood vessels is an essential task in automated analysis of retinopathy. This paper presents a new and effective vessel segmentation algorithm that features computational simplicity and fast implementation. This method uses morphological pre-processing to decrease the disturbance of bright structures and lesions before vessel extraction. Next, a vessel probability map is generated by computing the eigenvalues of the second derivatives of Gaussian filtered image at multiple scales. Then, the second order local entropy thresholding is applied to segment the vessel map. Lastly, a rule-based decision step, which measures the geometric shape difference between vessels and lesions is applied to reduce false positives. The algorithm is evaluated on the low-resolution DRIVE and STARE databases and the publicly available high-resolution image database from Friedrich-Alexander University Erlangen-Nuremberg (Germany). The proposed method achieved comparable performance to state of the art unsupervised vessel segmentation methods with a competitive faster speed on the DRIVE and STARE databases. For the high resolution fundus image database, the proposed algorithm outperforms an existing approach both on performance and speed. The efficiency and robustness make the blood vessel segmentation method described here suitable for broad application in automated analysis of retinal images.

Citation Download Citation

H. Yu, S. Barriga, C. Agurto, G. Zamora, W. Bauman, P. Soliz, "Fast vessel segmentation in retinal images using multi-scale enhancement and second-order local entropy", Proc. SPIE 8315, Medical Imaging 2012: Computer-Aided Diagnosis, 83151B (23 February 2012); doi: 10.1117/12.911547; https://doi.org/10.1117/12.911547

ACCESS THE FULL ARTICLE

PERSONAL SIGN IN
Full access may be available with your subscription

Email or Username Forgot your username?

Password Forgot your password?

Show

Remember Email/Username on this computer

Remember Password

No SPIE account? Create an account
or Institutional Sign In via Shibboleth

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $14.40

Non-members: $18.00 ADD TO CART

Show All Keywords

Keywords/Phrases

Search In:

Publication Years