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Optimal Diffusion T...
Optimal Diffusion Tensor Imaging with Repeated Measurements
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- Alipoor, Mohammad, 1983 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Gu, Irene Yu-Hua, 1953 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Mehnert, Andrew, 1967 (författare)
- Chalmers tekniska högskola,Chalmers University of Technology
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- Lilja, Y (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för klinisk neurovetenskap och rehabilitering,Institute of Neuroscience and Physiology, Department of Clinical Neuroscience and Rehabilitation,University of Gothenburg
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- Nilsson, Daniel, 1973 (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för neurovetenskap och fysiologi, sektionen för klinisk neurovetenskap och rehabilitering,Institute of Neuroscience and Physiology, Department of Clinical Neuroscience and Rehabilitation,University of Gothenburg
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(creator_code:org_t)
- Berlin, Heidelberg : Springer Berlin Heidelberg, 2013
- 2013
- Engelska.
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Ingår i: Lecture Notes in Computer Science: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2013. 16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings, Part I. - Berlin, Heidelberg : Springer Berlin Heidelberg. - 0302-9743 .- 1611-3349. - 9783642408106 ; 8149, s. 687-694
- Relaterad länk:
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http://dx.doi.org/10...
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https://gup.ub.gu.se...
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https://doi.org/10.1...
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https://research.cha...
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Abstract
Ämnesord
Stäng
- Several data acquisition schemes for diffusion MRI have been proposed and explored to date for the reconstruction of the 2nd order tensor. Our main contributions in this paper are: (i) the definition of a new class of sampling schemes based on repeated measurements in every sampling point; (ii) two novel schemes belonging to this class; and (iii) a new reconstruction framework for the second scheme. We also present an evaluation, based on Monte Carlo computer simulations, of the performances of these schemes relative to known optimal sampling schemes for both 2nd and 4th order tensors. The results demonstrate that tensor estimation by the proposed sampling schemes and estimation framework is more accurate and robust.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Information Systems (hsv//eng)
- TEKNIK OCH TEKNOLOGIER -- Medicinteknik -- Medicinsk bildbehandling (hsv//swe)
- ENGINEERING AND TECHNOLOGY -- Medical Engineering -- Medical Image Processing (hsv//eng)
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datorseende och robotik (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Vision and Robotics (hsv//eng)
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Neurologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Neurology (hsv//eng)
Nyckelord
- diffusion tensor imaging
- optimal sampling scheme
- tensor estimation
- optimal sampling scheme
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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