Derivation of pressure gradients from magnetic resonance angiography using multi-resolution segmentation
Derivation of pressure gradients from magnetic resonance angiography using multi-resolution segmentation
- Author(s): P.E. Summers and A.H. Bhalerao
- DOI: 10.1049/cp:19950690
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- Author(s): P.E. Summers and A.H. Bhalerao Source: Fifth International Conference on Image Processing and its Applications, 1995 p. 404 – 408
- Conference: Fifth International Conference on Image Processing and its Applications
- DOI: 10.1049/cp:19950690
- ISBN: 0 85296 642 3
- Location: Edinburgh, UK
- Conference date: 4-6 July 1995
- Format: PDF
The use of magnetic resonance (MR) angiography in cardiovascular assessment is steadily increasing on the merits of sensitivity to disease states, lack of ionising radiation and iodinated contrast agent, and widespread applicability to the vasculature. Because MR angiograms are usually obtained as a data set of parallel images, visualisation and analysis require post-processing. The sparsity of the macro-vasculature relative to the data volume. Coupled with the still variable results of MR studies has led to general very few widely used processing and viewing tools in clinical practice. We have implemented a model based multiresolution image segmentation technique which makes use of the velocity field information in phase contrast MR angiograms, and an a priori assumption that locally, blood vessels appear as line segments. The list structure of the resulting segmentation can be used efficiently in subsequent image analysis and processing. Within this segmentation, flow direction, vessel axis, diameter and velocity estimates can be made. We demonstrate its use in extracting vessels from patient data and in the calculation of pressure gradients in a model stenosis.
Inspec keywords: biomedical NMR; medical image processing; angiocardiography; image segmentation
Subjects: Patient diagnostic methods and instrumentation; Radiation and radioactivity applications in biomedicine; Medical magnetic resonance imaging and spectroscopy; Optical information, image and video signal processing
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