Efficient Excitation of Magnetization for Compressed Sensing MRI
- Technology Benefits
- Reduction in time needed for data acquisition.High SNR efficiency.Pseudorandom excitation, which approaches optimality for CS.Low RF power deposition (low specific absorption rate): relative to balanced SSFP, UCSD’s 2° RF pulses deposit approximately 15 times less RF power than the 30° pulses of balanced SSFP.Efficient use of gradients with simultaneous estimation of proton density, relaxation times, and resonance offset using CS methods.
- Technology Application
- This is a general approach to data acquisition for MRI and can potentially replace most existing MRI imaging strategies.
- Detailed Technology Description
- A UC San Diego (UCSD) researcher has developed a fast and efficient way to excite nuclear spins in the MR imaging process to generate randomly sampled data. The invention can potentially replace most existing MRI data acquisition strategies. The approach simultaneously produces high steady-state signal, high A/D duty cycle, and pseudo-random sampling functions, and is therefore both SNR efficient and readily amenable to CS reconstruction. The method also allows for extraction of proton density, T1, T2, and B0 maps from a single data set.The UCSD invention can achieve high information efficiency on data acquisition. It generates random transverse (observable) magnetization using very short random RF pulses (~10 microseconds each), applied approximately once every millisecond, with continuous gradients and data acquisition between RF pulses, for a time efficiency of 99 percent versus 20-50 percent for conventional balanced steady-state free precession (SSFP).The key methods consist of: A rapid train of random phase low-flip angle RF pulses can generate large steady state transverse magnetization.Gradients applied between these RF pulses that have a pseudorandom distribution weighted towards the center of k-space and will generate a distribution of coherences that result in a pseudorandom spatial pattern of excitation.
- Supplementary Information
- Patent Number: US7983040B2
Application Number: US2008256628A
Inventor: Campbell, Levi A. | Chu, Richard C. | Ellsworth, Jr., Michael J. | Iyengar, Madhusudan K. | Simons, Robert E.
Priority Date: 23 Oct 2008
Priority Number: US7983040B2
Application Date: 23 Oct 2008
Publication Date: 19 Jul 2011
IPC Current: H05K000720 | F28F000700 | H01L002334
US Class: 361699 | 0622592 | 1650804 | 1650805 | 16510433 | 1740151 | 174017LF | 257714 | 361727
Assignee Applicant: International Business Machines Corporationmonk
Title: Apparatus and method for facilitating pumped immersion-cooling of an electronic subsystem
Usefulness: Apparatus and method for facilitating pumped immersion-cooling of an electronic subsystem
Summary: Apparatus for facilitating cooling of electronic subsystem e.g. multi-blade center system of cooled electronic rack (claimed).
Novelty: Apparatus for facilitating cooling of electronic subsystem of cooled electronic rack, has coolant pump assembly that facilitates active pumping of coolant through container to provide pumped immersion-cooling of electronic subsystem
- Industry
- ICT/Telecom
- Sub Category
- IT System
- Application No.
- 9285445
- Others
-
State Of Development
The principles have been demonstrated with reconstruction of simulated data.
Related Materials
Available upon request.
- Wong EC Efficient Randomly Encoded Data Acquisition for Compressed 2010. ISMRM 18th Annual Meeting Abstract # 4893.
Tech ID/UC Case
21395/2010-262-0
Related Cases
2010-262-0
- *Abstract
-
Existing magnetic resonance imaging (MRI) methods are built around the 40-year old concept that MRI data should be the Fourier transform of the desired image. Compressed sensing (CS) technology for reconstructing images and other data from incomplete data has the potential to reduce MR data acquisition time. The ideal raw data for CS reconstruction is randomly sampled data rather than the Fourier sampled data used by the current technologies.
- *IP Issue Date
- Mar 15, 2016
- *Principal Investigator
-
Name: Eric Wong
Department:
Name: Eric Wong
Department:
- Country/Region
- USA
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