Paper doi abstract bibtex

Sequence optimization and appropriate sequence selection is still an unmet need in magnetic resonance ﬁngerprinting (MRF). The main challenge in MRF sequence design is the lack of an appropriate measure of the sequence's encoding capability. To ﬁnd such a measure, three different candidates for judging the encoding capability have been investigated: local and global dot-product-based measures judging dictionary entry similarity as well as a Monte Carlo method that evaluates the noise propagation properties of an MRF sequence. Consistency of these measures for different sequence lengths as well as the capability to predict actual sequence performance in both phantom and in vivo measurements was analyzed. While the dot-product-based measures yielded inconsistent results for different sequence lengths, the Monte Carlo method was in a good agreement with phantom experiments. In particular, the Monte Carlo method could accurately predict the performance of different ﬂip angle patterns in actual measurements. The proposed Monte Carlo method provides an appropriate measure of MRF sequence encoding capability and may be used for sequence optimization.

@article{sommer_towards_2017, title = {Towards predicting the encoding capability of {MR} fingerprinting sequences}, volume = {41}, issn = {0730725X}, url = {https://linkinghub.elsevier.com/retrieve/pii/S0730725X17301182}, doi = {10.1016/j.mri.2017.06.015}, abstract = {Sequence optimization and appropriate sequence selection is still an unmet need in magnetic resonance ﬁngerprinting (MRF). The main challenge in MRF sequence design is the lack of an appropriate measure of the sequence's encoding capability. To ﬁnd such a measure, three different candidates for judging the encoding capability have been investigated: local and global dot-product-based measures judging dictionary entry similarity as well as a Monte Carlo method that evaluates the noise propagation properties of an MRF sequence. Consistency of these measures for different sequence lengths as well as the capability to predict actual sequence performance in both phantom and in vivo measurements was analyzed. While the dot-product-based measures yielded inconsistent results for different sequence lengths, the Monte Carlo method was in a good agreement with phantom experiments. In particular, the Monte Carlo method could accurately predict the performance of different ﬂip angle patterns in actual measurements. The proposed Monte Carlo method provides an appropriate measure of MRF sequence encoding capability and may be used for sequence optimization.}, language = {en}, urldate = {2021-02-12}, journal = {Magnetic Resonance Imaging}, author = {Sommer, K. and Amthor, T. and Doneva, M. and Koken, P. and Meineke, J. and Börnert, P.}, month = sep, year = {2017}, pages = {7--14}, }

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