Efficient optimization of mri sampling patterns using the bayesian fisher information matrix
Standard
Efficient optimization of mri sampling patterns using the bayesian fisher information matrix. / Grosser, Mirco; Knopp, Tobias.
2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021. IEEE Computer Society, 2021. S. 234-237 9434109 (Proceedings - International Symposium on Biomedical Imaging; Band 2021-April).Publikationen: SCORING: Beitrag in Buch/Sammelwerk › Konferenzbeitrag - Aufsatz in Konferenzband › Forschung › Begutachtung
Harvard
APA
Vancouver
Bibtex
}
RIS
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 -