Reduced Encoding Diffusion Spectrum Imaging Implemented With a Bi-Gaussian Model

Diffusion spectrum imaging (DSI) can map complex fiber microstructures in tissues by characterizing their 3-D water diffusion spectra. However, a long acquisition time is required for adequate -space sampling to completely reconstruct the 3-D diffusion probability density function. Furthermore, to achieve a high -value encoding for sufficient spatial resolution, the diffusion gradient duration and the diffusion time are usually lengthened on a clinical scanner, resulting in a long echo time and low signal-to-noise ratio of diffusion-weighted images. To bypass long acquisition times and strict gradient requirements, the reduced-encoding DSI (RE-DSI) with a bi-Gaussian diffusion model is presented in this study. The bi-Gaussian extrapolation kernel, based on the assumption of the bi-Gaussian diffusion signal curve across biological tissue, is applied to the reduced -space sampling data in order to fulfill the high -value requirement. The crossing phantom model and the manganese-enhanced ...

• Type: Journal
• Year: 2008
• Where: TMI
• Authors: Chun-Hung Yeh, Kuan-Hung Cho, Hsuan-Cheng Lin, Jiun-Jie Wang, Ching-Po Lin
• Keywords: Acquisition Time, Diffusion, Long Acquisition Times, TMI 2008