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Automatic Segmentation of Blood Vessels from Dynamic MRI Datasets

  • Olga Kubassova
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4791)

Abstract

In this paper we present an approach for blood vessel segmentation from dynamic contrast-enhanced MRI datasets of the hand joints acquired from patients with active rheumatoid arthritis. Exclusion of the blood vessels is needed for accurate visualisation of the activation events and objective evaluation of the degree of inflammation. The segmentation technique is based on statistical modelling motivated by the physiological properties of the individual tissues, such as speed of uptake and concentration of the contrast agent; it incorporates Markov random field probabilistic framework and principal component analysis. The algorithm was tested on 60 temporal slices and has shown promising results.

Keywords

Segmentation Technique Deformable Model Vessel Segmentation Hand Joint Blood Vessel Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Olga Kubassova
    • 1
  1. 1.School of Computing, University of LeedsUK

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