Multidimensional magnetic resonance imaging: new methods for analysis of cardiovascular dynamics
2003 (English)Doctoral thesis, comprehensive summary (Other academic)
Cardiovascular flow and motion occur in three-dimensional (3D) space and vary dynamically over the cardiac cycle. The description of these complicated patterns using non-invasive imaging requires new tools for data acquisition, processing and visualization. In this thesis, a number of techniques are presented, all of which aim at improving the description of multidimensional cardiovascular flow and motion.
For the study of cardiac motion, a new M-mode method was developed that uses time-resolved image data to retrospectively calculate an M-mode image along an arbitrary line. This reduces the dimensionality of the acquired image data to one dimension plus time, which facilitates the analysis of the motion of cardiac structures. In order to describe flow patterns within the heart and great vessels, phase contrast magnetic resonance imaging (MRI) can be used to accurately measure velocities. Existing techniques for the acquisition of phase contrast data were extended in order to acquire time-resolved 3D image data that contain information about all three velocity components in each voxel. A number of possible approaches for reducing the scan time required were applied. Reducing the scan time in MRI often results in images with a poor signal-to-noise ratio (SNR). Image processing techniques were therefore investigated that utilize adaptive filtering in order to reduce the noise level, while still preserving the details of small structures. Once multidimensional image data are acquired, there is an immediate need to visualize the data in a comprehensible way. Particle trace visualization of velocity vector data was applied in order to study flow patterns in the human heart. Using these methods, completely new insights into the patterns of blood flow within the left atrium were achieved. This and future applications are made possible by the powerful combination of massive multidimensional data sets and tools developed specifically for the complicated conditions of cardiovascular flow.
Place, publisher, year, edition, pages
Linköping: Linköpings universitet , 2003. , 74 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 807
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:liu:diva-29438Local ID: 14784ISBN: 91-7373-616-3OAI: oai:DiVA.org:liu-29438DiVA: diva2:250253
2003-04-29, Föreläsningssal Conrad, Universitetssjukhuset, Linköping, 13:15 (Swedish)
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