Efficient optimization of mri sampling patterns using the bayesian fisher information matrix

TY - CHAP

T1 - Efficient optimization of mri sampling patterns using the bayesian fisher information matrix

AU - Grosser, Mirco

AU - Knopp, Tobias

N1 - Publisher Copyright: © 2021 IEEE.

PY - 2021/4/13

Y1 - 2021/4/13

N2 - This work proposes an efficient way to adapt MRI sampling patterns to a given anatomy and imaging context using a small set of representative training data. Such techniques were shown to help shorten MRI experiments while guaranteeing high image quality. An often encountered drawback of such methods are high computation times. We extend the recently proposed OEDIPUS framework by making use of the Bayesian Fisher information matrix. Based on the latter we devise an algorithm, which can be more than an order of magnitude faster than OEDIPUS for practical applications. This opens up the possibility to generate tailored sampling patterns for applications for which this would be infeasible otherwise. We evaluate our method in the context of multi-echo gradient echo imaging. The resulting sampling patterns show superior image reconstruction results compared to those obtained by other popularly used sampling schemes.

AB - This work proposes an efficient way to adapt MRI sampling patterns to a given anatomy and imaging context using a small set of representative training data. Such techniques were shown to help shorten MRI experiments while guaranteeing high image quality. An often encountered drawback of such methods are high computation times. We extend the recently proposed OEDIPUS framework by making use of the Bayesian Fisher information matrix. Based on the latter we devise an algorithm, which can be more than an order of magnitude faster than OEDIPUS for practical applications. This opens up the possibility to generate tailored sampling patterns for applications for which this would be infeasible otherwise. We evaluate our method in the context of multi-echo gradient echo imaging. The resulting sampling patterns show superior image reconstruction results compared to those obtained by other popularly used sampling schemes.

KW - Compressed sensing

KW - Experiment Design

KW - MRI

UR - http://www.scopus.com/inward/record.url?scp=85107211957&partnerID=8YFLogxK

U2 - 10.1109/ISBI48211.2021.9434109

DO - 10.1109/ISBI48211.2021.9434109

M3 - Conference contribution - Article for conference

AN - SCOPUS:85107211957

T3 - Proceedings - International Symposium on Biomedical Imaging

SP - 234

EP - 237

BT - 2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021

PB - IEEE Computer Society

T2 - 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021

Y2 - 13 April 2021 through 16 April 2021

ER -