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Proceedings Paper

A linking framework for pixel classification based retinal vessel segmentation
Author(s): Meindert Niemeijer; Bram van Ginneken; Michael D. Abràmoff M.D.
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Paper Abstract

Retinal vessel segmentation is a prerequisite for the analysis of vessel parameters such as tortuosity, variation of the vessel width along the vessel and the ratio between the venous and arterial vessel width. This analysis can provide indicators for the presence of a wide range of diseases. Different types of approaches have been proposed to segment the retinal vasculature and two important groups are vessel tracking and pixel processing based methods. An advantage of tracking based methods is the guaranteed connectedness of vessel segments, in pixel processing based methods connectedness is not guaranteed. In this work an automated vessel linking framework is presented. The framework links together separate pieces of the retinal vasculature into a connected vascular tree. To determine which vessel sections should be linked together the use of a supervised cost function is proposed. Evaluation is performed on the vessel centerlines. The results show that the vessel linking framework outperforms other automated vessel linking methods especially for the narrowest vessels.

Paper Details

Date Published: 27 February 2009
PDF: 8 pages
Proc. SPIE 7262, Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging, 726216 (27 February 2009); doi: 10.1117/12.811653
Show Author Affiliations
Meindert Niemeijer, The Univ. of Iowa (United States)
Bram van Ginneken, Univ. Medical Ctr. Utrecht (Netherlands)
Michael D. Abràmoff M.D., The Univ. of Iowa (United States)

Published in SPIE Proceedings Vol. 7262:
Medical Imaging 2009: Biomedical Applications in Molecular, Structural, and Functional Imaging
Xiaoping P. Hu; Anne V. Clough, Editor(s)

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