RT info:eu-repo/semantics/conferenceObject
T1 Optimal Diffusion-weighting Gradient Waveform Design (ODGD): Formulation and Experimental Validation
A1 Peña Nogales, Óscar
A1 Zhang, Yuxin
A1 Luis García, Rodrigo de
A1 Aja Fernández, Santiago
A1 H. Holmes, James
A1 Hernando, Diego
AB Diffusion-Weighted MRI often suffers from signal attenuation due to long TE, sensitivity to physiological motion, and dephasing due to concomitant gradients (CGs). These challenges complicate image interpretation and may introduce bias in quantitative diffusion measurements. Motion moment-nulled diffusion-weighting gradients have been proposed to compensate motion, however, they frequently result in high TE and suffer from CG effects. In this work, the Optimal Diffusion-weighting Gradient waveform Design method that overcomes limitations of state-of-the-art waveforms is revisited and validated in phantom and in-vivo experiments. These diffusion-weighting gradient waveforms reduce the TE and increase the SNR of state-of-the-art waveforms without and with CG-nulling.
YR 2018
FD 2018
LK http://uvadoc.uva.es/handle/10324/31375
UL http://uvadoc.uva.es/handle/10324/31375
LA eng
NO International Society of Magnetic Resonance in Medicine 26th Annual, Paris,2018
DS UVaDOC
RD 22-dic-2024