The purpose of this Technical Research and Development (TR&D) Project is the development and dissemination of technical tools for MR imaging pulse sequence development. This includes RF pulse design, pulse sequence waveform and acquisition design, and image reconstruction algorithms and software. Most of this technology is originally developed in either NIH or industrial supported projects. This TR&D provides the support for the refinement of these technologies, and translation into more general, widely useable toolboxes and software. In addition, data sets are provided, so that other investigators can reproduce the results from the original papers, and directly compare their work to our algorithms. This greatly expands the universe of investigators that can contribute to MR imaging research. The response has been tremendous, with many hundreds to thousands of downloads for each software package. For example, the sparse reconstruction matlab code has been downloaded 1840 times in the last year and half, and the paper describing these algorithms is the most downloaded paper over the last five years in Magnetic Resonance in Medicine, the leading journal for MR imaging research.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Biotechnology Resource Grants (P41)
Project #
5P41EB015891-25
Application #
9689545
Study Section
Special Emphasis Panel (ZEB1)
Project Start
Project End
2021-03-31
Budget Start
2019-04-01
Budget End
2020-03-31
Support Year
25
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Stanford University
Department
Type
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94305
Han, Amy Kyungwon; Bae, Jung Hwa; Gregoriou, Katerina C et al. (2018) MR-Compatible Haptic Display of Membrane Puncture in Robot-Assisted Needle Procedures. IEEE Trans Haptics :
Levine, Evan; Stevens, Kathryn; Beaulieu, Christopher et al. (2018) Accelerated three-dimensional multispectral MRI with robust principal component analysis for separation of on- and off-resonance signals. Magn Reson Med 79:1495-1505
Winkler, Simone A; Schmitt, Franz; Landes, Hermann et al. (2018) Gradient and shim technologies for ultra high field MRI. Neuroimage 168:59-70
Gu, Meng; Hurd, Ralph; Noeske, Ralph et al. (2018) GABA editing with macromolecule suppression using an improved MEGA-SPECIAL sequence. Magn Reson Med 79:41-47
Perkins, Stephanie L; Daniel, Bruce L; Hargreaves, Brian A (2018) MR imaging of magnetic ink patterns via off-resonance sensitivity. Magn Reson Med 80:2017-2023
Lee, Brian J; Grant, Alexander M; Chang, Chen-Ming et al. (2018) MR Performance in the Presence of a Radio Frequency-Penetrable Positron Emission Tomography (PET) Insert for Simultaneous PET/MRI. IEEE Trans Med Imaging 37:2060-2069
Kogan, Feliks; Levine, Evan; Chaudhari, Akshay S et al. (2018) Simultaneous bilateral-knee MR imaging. Magn Reson Med 80:529-537
Gibbons, Eric K; Le Roux, Patrick; Pauly, John M et al. (2018) Slice profile effects on nCPMG SS-FSE. Magn Reson Med 79:430-438
Chen, Feiyu; Taviani, Valentina; Malkiel, Itzik et al. (2018) Variable-Density Single-Shot Fast Spin-Echo MRI with Deep Learning Reconstruction by Using Variational Networks. Radiology 289:366-373
Chaudhari, Akshay S; Fang, Zhongnan; Kogan, Feliks et al. (2018) Super-resolution musculoskeletal MRI using deep learning. Magn Reson Med 80:2139-2154

Showing the most recent 10 out of 151 publications