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Flow quantification from time resolved three dimensional phase contrast MRI
Linköping University, Department of Medicine and Care, Center for Medical Image Science and Visualization. Linköping University, Faculty of Health Sciences.
Department of Medicine, University of California, San Francisco, USA.
Linköping University, Department of Medicine and Care. Linköping University, Department of Biomedical Engineering. Linköping University, Faculty of Health Sciences.ORCID iD: 0000-0001-5526-2399
(English)Manuscript (preprint) (Other academic)
Abstract [en]

This paper presents novel techniques for deriving meaningful quantitative parameters from three dimensional velocity measurements. By shifting perspective from the Eulerian grid of measured velocities to a Lagrange perspective that follows flow using particle traces, we are able to divide flow into different groups based on their behavior. Parameters from each group can then be extracted and quantified. The applicability of the method is demonstrated by extracting parameters of diastolic flow in the human left ventricle.

Keyword [en]
Flow quantification, velocity measurements, particle trace, left ventricle
National Category
Medical and Health Sciences
URN: urn:nbn:se:liu:diva-86176OAI: diva2:575358
Available from: 2012-12-10 Created: 2012-12-10 Last updated: 2016-03-14
In thesis
1. Automated feature detection in multidimensional images
Open this publication in new window or tab >>Automated feature detection in multidimensional images
2005 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Manual identification of structures and features in multidimensional images is at best time consuming and operator dependent. Feature identification need to be accurate, repeatable and quantitative.

This thesis presents novel methods for automated feature detection in multidimensional images that are independent on imaging modality. Feature detection is described at two abstraction levels. At the first low level the image is regionally processed to find local or regional features. In the second medium level results are taken from the low level feature detection and grouped into objects or parts that can be quantified. A key to quantification of cardiac function is delineation of the cardiac walls which is a difficult task. Two different methods are described and evaluated for delineation of the left ventricular wall from anatomical images. The results show that semi-automatic delineation is a huge time saver compared to manual delineation. To obtain a robust results as much a priori and image information as possible should be used in the delineation process. Regional cardiac wall function is further studied by deriving and analyzing strain-rate tensors from velocity encoded images. For flow encoded images novel methods to find regional flow structures such as vortex cores, flow based delineation, and flow quantification are proposed. These methods are applied to study blood flow in the human heart, but the techniques outlined are general and can be applied to a wide array of flow conditions.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2005. 70 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 917
National Category
Medical and Health Sciences
urn:nbn:se:liu:diva-29497 (URN)14852 (Local ID)91-85297-10-0 (ISBN)14852 (Archive number)14852 (OAI)
Public defence
2005-04-15, Elsa Brändströmsalen, Campus US, Linköpings Universitet, Linköping, 13:00 (English)
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2012-12-10Bibliographically approved

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Heiberg, EinarKarlsson, Matts
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Center for Medical Image Science and VisualizationFaculty of Health SciencesDepartment of Medicine and CareDepartment of Biomedical Engineering
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