Abstract
In diffusion-weighted MRI, general gradient waveforms became of interest for their sensitivity to microstructure features of the brain white matter. However, the design of such waveforms remains an open problem. In this work, we propose a framework for generalized gradient waveform design with optimized sensitivity to selected microstructure features. In particular, we present a rotation-invariant method based on a genetic algorithm to maximize the sensitivity of the signal to the intra-axonal volume fraction. The sensitivity is evaluated by computing a score based on the Fisher information matrix from Monte-Carlo simulations, which offer greater flexibility and realism than conventional analytical models. As proof of concept, we show that the optimized waveforms have higher scores than the conventional pulsed-field gradients experiments. Finally, the proposed framework can be generalized to optimize the waveforms for to any microstructure feature of interest.
Original language | English |
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Title of host publication | Medical Image Computing and Computer Assisted Intervention |
Editors | Anne L. Martel, Purang Abolmaesumi, Danail Stoyanov, Diana Mateus, Maria A. Zuluaga, S. Kevin Zhou, Daniel Racoceanu, Leo Joskowicz |
Publisher | Springer |
Publication date | 2020 |
Pages | 94-103 |
ISBN (Print) | 9783030597122 |
DOIs | |
Publication status | Published - 2020 |
Event | 23rd International Conference on Medical Image Computing and Computer Assisted Intervention - Online Event, Lima, Peru Duration: 4 Oct 2020 → 8 Oct 2020 https://www.miccai2020.org/ |
Conference
Conference | 23rd International Conference on Medical Image Computing and Computer Assisted Intervention |
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Location | Online Event |
Country/Territory | Peru |
City | Lima |
Period | 04/10/2020 → 08/10/2020 |
Internet address |
Series | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 12262 LNCS |
ISSN | 0302-9743 |
Keywords
- Acquisition design
- Diffusion MRI
- Fisher information
- Generalized gradient waveforms
- Monte-Carlo simulations