Design and Implementation of Calculated Readout by Spectral Parallelism (CRISP) in Magnetic Resonance Imaging (MRI)
MetadataShow full item record
CRISP is a data acquisition and image reconstruction technique that offers theoretical increases in signal-to-noise ratio (SNR) and dynamic range over traditional methods in magnetic resonance imaging (MRI). The incoming broadband MRI signal is de-multiplexed into multiple narrow frequency bands using analog filters. Signal from each narrowband channel is then individually captured and digitized. The original signal is recovered by recombining all the channels via weighted addition, where the weights correspond to the frequency responses of each narrowband filter. With ideal bandpasses and bandwidth dependent noise after filtering, SNR increase is proportional to sqrt(N), where N is the number of bandpasses. In addition to SNR improvement, free induction decay (FID) echoes in CRISP experience a slower decay rate. In situations where resolution is limited by digitization noise, CRISP is able to capture data further out into the higher frequency regions of k-space, which leads to a relative increase in resolution. The conversion from one broadband MR signal into multiple narrowband channels is realized using a comb or bank of active analog bandpass filters. A custom CRISP RF receiver chain is implemented to downconvert and demodulate the raw MR signal prior to narrowband filtering, and to digitize the signals from each filter channel simultaneously. Results are presented demonstrating that the CRISP receiver chain can acquire 2D MR images (without narrowband filters) with SNR similar to SNR of images obtained with a clinical system. Acquiring 2D CRISP images (with narrowband filters) was not possible due to the lack of phase lock between rows in k-space. RMS noise of narrowband, broadband and unfiltered 1D echoes are compared.
Cite this work
Simon Sai-Man So (2010). Design and Implementation of Calculated Readout by Spectral Parallelism (CRISP) in Magnetic Resonance Imaging (MRI). UWSpace. http://hdl.handle.net/10012/5215