MATI: A GPU-Accelerated Toolbox for Microstructural Diffusion MRI Simulation and Data Fitting with a User-Friendly GUI
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866915008151027712 |
|---|---|
| author | Xu, Junzhong Devan, Sean P. Shi, Diwei Pamulaparthi, Adithya Yan, Nicholas Zu, Zhongliang Smith, David S. Harkins, Kevin D. Gore, John C. Jiang, Xiaoyu |
| author_facet | Xu, Junzhong Devan, Sean P. Shi, Diwei Pamulaparthi, Adithya Yan, Nicholas Zu, Zhongliang Smith, David S. Harkins, Kevin D. Gore, John C. Jiang, Xiaoyu |
| contents | MATI (Microstructural Analysis Toolbox for Imaging) is a versatile MATLAB-based toolbox that combines both simulation and data fitting capabilities for microstructural dMRI research. It provides a user-friendly, GUI-driven interface that enables researchers, including those without programming experience, to perform advanced MRI simulations and data analyses. For simulation, MATI supports arbitrary microstructural modeled tissues and pulse sequences. For data fitting, MATI supports a range of fitting methods including traditional non-linear least squares, Bayesian approaches, machine learning, and dictionary matching methods, allowing users to tailor analyses based on specific research needs. Optimized with vectorized matrix operations and high-performance numerical libraries, MATI achieves high computational efficiency, enabling rapid simulations and data fitting on CPU and GPU hardware. While designed for microstructural dMRI, MATI's generalized framework can be extended to other imaging methods, making it a flexible and scalable tool for quantitative MRI research. By enhancing accessibility and efficiency, MATI offers a significant step toward translating advanced imaging techniques into clinical applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_04401 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MATI: A GPU-Accelerated Toolbox for Microstructural Diffusion MRI Simulation and Data Fitting with a User-Friendly GUI Xu, Junzhong Devan, Sean P. Shi, Diwei Pamulaparthi, Adithya Yan, Nicholas Zu, Zhongliang Smith, David S. Harkins, Kevin D. Gore, John C. Jiang, Xiaoyu Medical Physics MATI (Microstructural Analysis Toolbox for Imaging) is a versatile MATLAB-based toolbox that combines both simulation and data fitting capabilities for microstructural dMRI research. It provides a user-friendly, GUI-driven interface that enables researchers, including those without programming experience, to perform advanced MRI simulations and data analyses. For simulation, MATI supports arbitrary microstructural modeled tissues and pulse sequences. For data fitting, MATI supports a range of fitting methods including traditional non-linear least squares, Bayesian approaches, machine learning, and dictionary matching methods, allowing users to tailor analyses based on specific research needs. Optimized with vectorized matrix operations and high-performance numerical libraries, MATI achieves high computational efficiency, enabling rapid simulations and data fitting on CPU and GPU hardware. While designed for microstructural dMRI, MATI's generalized framework can be extended to other imaging methods, making it a flexible and scalable tool for quantitative MRI research. By enhancing accessibility and efficiency, MATI offers a significant step toward translating advanced imaging techniques into clinical applications. |
| title | MATI: A GPU-Accelerated Toolbox for Microstructural Diffusion MRI Simulation and Data Fitting with a User-Friendly GUI |
| topic | Medical Physics |
| url | https://arxiv.org/abs/2411.04401 |