Evaluation of blood vessel detection methods

R. Sadeghzadeh; M. Berks; S. M. Astley; C. J. Taylor

doi:10.1117/12.878723

14 March 2011 Evaluation of blood vessel detection methods

R. Sadeghzadeh, M. Berks, S. M. Astley, C. J. Taylor

Proceedings Volume 7962, Medical Imaging 2011: Image Processing; 79623U (2011) https://doi.org/10.1117/12.878723
Event: SPIE Medical Imaging, 2011, Lake Buena Vista (Orlando), Florida, United States

Abstract

We address the problem of evaluating the performance of algorithms for detecting curvilinear structures in medical images. As an exemplar we consider the detection of vessel trees which contain structures of variable width and contrast. Results for the conventional approach to evaluation, in which the detector output is compared directly with a groundtruth mask, tend to be dominated by the detection of large vessels and fail to capture adequately whether or not finer, lower contrast vessels have been detected successfully. We propose and investigate three alternative evaluation strategies. We demonstrate the use of the standard and new evaluation strategies to assess the performance of a novel method for detecting vessels in retinograms, using the publicly available DRIVE database.

Citation Download Citation

R. Sadeghzadeh, M. Berks, S. M. Astley, and C. J. Taylor "Evaluation of blood vessel detection methods", Proc. SPIE 7962, Medical Imaging 2011: Image Processing, 79623U (14 March 2011); https://doi.org/10.1117/12.878723

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KEYWORDS

Tolerancing

Blood vessels

Wavelets

Image segmentation

Databases

Medical imaging

Detection and tracking algorithms

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