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. © Springer-Verlag Berlin Heidelberg 2007.
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CITATION STYLE
Kubassova, O. (2007). Automatic segmentation of blood vessels from dynamic MRI datasets. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4791 LNCS, pp. 593–600). Springer Verlag. https://doi.org/10.1007/978-3-540-75757-3_72
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