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Clustering of tenso...
Clustering of tensor votes for inference of fibre orientations in DTI data
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- Jörgens, Daniel, 1988- (author)
- KTH,Medicinsk bildbehandling och visualisering
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- Smedby, Örjan, 1956- (author)
- KTH,Medicinsk bildbehandling och visualisering
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- Moreno, Rodrigo, 1973- (author)
- KTH,Medicinsk bildbehandling och visualisering
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(creator_code:org_t)
- 2016
- 2016
- English.
- Related links:
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https://urn.kb.se/re...
Abstract
Subject headings
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- mong the various diffusion MRI techniques, diffusion ten-sor imaging (DTI) is still most commonly used in clinicalpractice in order to investigate connectivity and fibre anatomyin the human brain. Besides its apparent advantages of a shortacquisition time and noise robustness compared to other tech-niques, it suffers from its major weakness of assuming a sin-gle fibre model in each voxel. This constitutes a problem forDTI fibre tracking algorithms in regions with crossing fibres.Methods approaching this problem in a postprocessing stepemploy diffusion-like techniques to correct the directional in-formation. We propose an extension of tensor voting in whichinformation from voxels with a single fibre is used to inferorientation distributions in multi fibre voxels. The method isable to resolve multiple fibre orientations by clustering tensorvotes instead of adding them up. Moreover, a new vote cast-ing procedure is proposed which is appropriate even for smallneighbourhoods. To account for the locality of DTI data, weuse a small neighbourhood for distributing information at atime, but apply the algorithm iteratively to close larger gaps.The method shows promising results in both synthetic casesand for processing DTI-data of the human brain.
Subject headings
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
Keyword
- DTI
- tensor voting
- spherical clustering
Publication and Content Type
- vet (subject category)
- kon (subject category)
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