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Proceedings Paper

Flow-based segmentation of the large thoracic arteries in tridirectional phase-contrast MRI
Author(s): Michael Schmidt; Roland Unterhinninghofen; Sebastian Ley; Rüdiger Dillmann
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Paper Abstract

Tridirectional Phase-Contrast (PC)-MRI sequences provide spatially and temporally resolved measurements of blood flow velocity vectors in the human body. Analyzing flow conditions based on these datasets requires prior segmentation of the vessels of interest. In view of decreased quality of morphology images in PC-MRI sequences, the flow data provides valuable information to support reliable segmentation. This work presents a semi-automatic approach for segmenting the large arteries utilizing both morphology and flow information. It consists of two parts, the extraction of a simplified vessel model based on vessel centerlines and diameters, and a following refinement of the resulting surface for each time frame. Vessel centerlines and diameters are extracted using an offset adaptive medialness function that estimates a voxel's likelihood of belonging to a vessel centerline. The resulting centerline model is manually post-processed to select the appropriate centerlines and link possible gaps. The surface described by the final centerline model is used to initialize a 3D level set segmentation of each time frame. Deformation velocities that depend on both morphology and flow information are proposed and a new approach to account for the curved shape of vessels is introduced. The described segmentation system has been successfully applied on a total of 22 datasets of the thoracic aorta and the pulmonary arteries. Resulting segmentations have been assessed by an expert radiologist and were considered to be very satisfactory.

Paper Details

Date Published: 27 March 2009
PDF: 10 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 725914 (27 March 2009); doi: 10.1117/12.812238
Show Author Affiliations
Michael Schmidt, Univ. of Karlsruhe (Germany)
Roland Unterhinninghofen, Univ. of Karlsruhe (Germany)
Sebastian Ley, Univ. Hospital Heidelberg (Germany)
Rüdiger Dillmann, Univ. of Karlsruhe (Germany)

Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)

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