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Towards Optimal Sampling in Diffusion MRI
Linköping University, Department of Biomedical Engineering, Division of Biomedical Engineering. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-9091-4724
2019 (English)In: COMPUTATIONAL DIFFUSION MRI (CDMRI 2018), SPRINGER-VERLAG BERLIN , 2019Conference paper, Published paper (Refereed)
Abstract [en]

The methodology outlined in this chapter is intended to provide a tool for the generation of sets of MRI diffusion encoding waveforms that are optimal for tissue micro-structure estimation. The methodology presented has five distinct components: 1. Defining the class of waveforms allowed, i.e. defining the measurement space. 2. Specifying the expected distribution of microstructure features present in the targeted tissue. 3. Learning the metric in the chosen measurement space. 4. Designing a continuous parametric functional suitable for approximation of the estimated metric. 5. Finding a distribution of a chosen number of waveforms that is optimal given the continuous metric. The tissue is modeled as a collection of simple elliptical compartments with varying size and shape. Two waveform classes are tested: The classical Stejskal-Tanner waveform and an idealized Laun long-short waveform. The estimation of the metric is based on correlations between measurements obtained at given points in the measurement space using an information theoretical approach. Optimal sets of waveforms are found using a simulated annealing inspired energy minimizing approach. The superior performance of the methodology is demonstrated for a number of different cases by means of simulations.

Place, publisher, year, edition, pages
SPRINGER-VERLAG BERLIN , 2019.
Series
Mathematics and Visualization, ISSN 1612-3786
Keywords [en]
Learning; Sample space metric; Optimal waveform sets
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-161867DOI: 10.1007/978-3-030-05831-9_1ISI: 000493062700001ISBN: 978-3-030-05831-9 (electronic)ISBN: 978-3-030-05830-2 (print)OAI: oai:DiVA.org:liu-161867DiVA, id: diva2:1370862
Conference
21st International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI) / 8th Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM) / International Workshop on Computational Diffusion MRI (CDMRI)
Note

Funding Agencies|Swedish Research CouncilSwedish Research Council [2015-05356]; Swedish Foundation for Strategic ResearchSwedish Foundation for Strategic Research [AM13-0090]; Linneaus center CADICS; Wallenberg foundation Seeing Organ Function

Available from: 2019-11-18 Created: 2019-11-18 Last updated: 2019-11-18

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