@article {997,
	title = {Optimisation of quantitative brain diffusion-relaxation MRI acquisition protocols with physics-informed machine learning},
	journal = {Medical Image Analysis},
	volume = {94},
	year = {2024},
	pages = {103134},
	abstract = {<p>Diffusion-relaxation MRI aims to extract quantitative measures that characterise microstructural tissue properties such as orientation, size, and shape, but long acquisition times are typically required. This work proposes a physics-informed learning framework to extract an optimal subset of diffusion-relaxation MRI measurements for enabling shorter acquisition times, predict non-measured signals, and estimate quantitative parameters. In vivo and synthetic brain 5D-Diffusion-T1-T2*-weighted MRI data obtained from five healthy subjects were used for training and validation, and from a sixth participant for testing. One fully data-driven and two physics-informed machine learning methods were implemented and compared to two manual selection procedures and Cram{\'e}rRao lower bound optimisation. The physics-informed approaches could identify measurement-subsets that yielded more consistently accurate parameter estimates in simulations than other approaches, with similar signal prediction error. Five-fold shorter protocols yielded error distributions of estimated quantitative parameters with very small effect sizes compared to estimates from the full protocol. Selected subsets commonly included a denser sampling of the shortest and longest inversion time, lowest echo time, and high b-value. The proposed framework combining machine learning and MRI physics offers a promising approach to develop shorter imaging protocols without compromising the quality of parameter estimates and signal predictions.</p>
},
	keywords = {Brain, Diffusion-relaxation, Quantitative MRI, machine learning},
	issn = {1361-8415},
	doi = {https://doi.org/10.1016/j.media.2024.103134},
	url = {https://www.sciencedirect.com/science/article/pii/S1361841524000598},
	author = {{\'A}lvaro Planchuelo-G{\'o}mez and Maxime Descoteaux and Hugo Larochelle and Jana Hutter and Derek K. Jones and Chantal M.W. Tax}
}
@article {956,
	title = {Anisotropy measure from three diffusion-encoding gradient directions},
	journal = {Magnetic Resonance Imaging},
	volume = {88},
	year = {2022},
	month = {2022},
	pages = {38{\textendash}43},
	author = {Santiago Aja-Fern{\'a}ndez and Guillem Par{\'\i}s and Carmen Mart{\'\i}n-Mart{\'\i}n and Derek K. Jones and AntonioTrist{\'a}n-Vega}
}
@article {899,
	title = {Apparent propagator anisotropy from single-shell diffusion MRI acquisitions},
	journal = {Magnetic Resonance in Medicine},
	volume = {85},
	year = {2021},
	month = {2021},
	pages = {2869-2881},
	chapter = {2869},
	doi = {https://doi.org/10.1002/mrm.28620},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.28620},
	author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Derek K. Jones}
}
@article {933,
	title = {On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge},
	journal = {NeuroImage},
	year = {2021},
	month = {2021},
	pages = {118367},
	issn = {1053-8119},
	doi = {https://doi.org/10.1016/j.neuroimage.2021.118367},
	url = {https://www.sciencedirect.com/science/article/pii/S1053811921006431},
	author = {Alberto De Luca and Andrada Ianus and Alexander Leemans and Marco Palombo and Noam Shemesh and Hui Zhang and Daniel C. Alexander and Markus Nilsson and Martijn Froeling and Geert-Jan Biessels and Mauro Zucchelli and Matteo Frigo and Enes Albay and Sara Sedlar and Abib Alimi and Samuel Deslauriers-Gauthier and Rachid Deriche and Rutger Fick and Maryam Afzali and Tomasz Pieciak and Fabian Bogusz and Santiago Aja-Fern{\'a}ndez and Evren {\"O}zarslan and Derek K. Jones and Haoze Chen and Mingwu Jin and Zhijie Zhang and Fengxiang Wang and Vishwesh Nath and Prasanna Parvathaneni and Jan Morez and Jan Sijbers and Ben Jeurissen and Shreyas Fadnavis and Stefan Endres and Ariel Rokem and Eleftherios Garyfallidis and Irina Sanchez and Vesna Prchkovska and Paulo Rodrigues and Bennet A. Landman and Kurt G. Schilling}
}
@article {912,
	title = {On the generalizability of diffusion MRI signal representations across acquisition parameters, sequences and tissue types: chronicles of the MEMENTO challenge},
	journal = {bioRxiv},
	year = {2021},
	month = {2021},
	doi = {10.1101/2021.03.02.433228},
	url = {https://www.biorxiv.org/content/early/2021/03/02/2021.03.02.433228},
	author = {De Luca, Alberto and Ianus, Andrada and Leemans, Alexander and Palombo, Marco and Shemesh, Noam and Zhang, Hui and Alexander, Daniel C and Nilsson, Markus and Froeling, Martijn and Biessels, Geert-Jan and Zucchelli, Mauro and Frigo, Matteo and Albay, Enes and Sedlar, Sara and Alimi, Abib and Deslauriers-Gauthier, Samuel and Deriche, Rachid and Fick, Rutger and Maryam Afzali and Tomasz Pieciak and Bogusz, Fabian and Santiago Aja-Fern{\'a}ndez and Ozarslan, Evren and Derek K. Jones and Chen, Haoze and Jin, Mingwu and Zhang, Zhijie and Wang, Fengxiang and Nath, Vishwesh and Parvathaneni, Prasanna and Morez, Jan and Sijbers, Jan and Jeurissen, Ben and Fadnavis, Shreyas and Endres, Stefan and Rokem, Ariel and Garyfallidis, Eleftherios and Sanchez, Irina and Prchkovska, Vesna and Rodrigues, Paulo and Landman, Bennet A and Schilling, Kurt G}
}
@inbook {895,
	title = {Alternative Diffusion Anisotropy Metric from Reduced MRI Acquisitions},
	booktitle = {Computational Diffusion MRI},
	year = {2020},
	pages = {13{\textendash}24},
	publisher = {Springer, Cham},
	organization = {Springer, Cham},
	author = {Santiago Aja-Fern{\'a}ndez and Antonio Trist{\'a}n-Vega and Rodrigo de Luis-Garc{\'\i}a and Derek K. Jones}
}
@article {839,
	title = {Direction-averaged diffusion-weighted MRI signal using different axisymmetric B-tensor encoding schemes},
	journal = {Magnetic Resonance in Medicine},
	volume = {n/a},
	year = {2020},
	month = {2020},
	keywords = {B-tensor encoding, diffusion-weighted~MRI, direction-averaged diffusion signal, high b-value, power-law},
	doi = {10.1002/mrm.28191},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.28191},
	author = {Maryam Afzali and Santiago Aja-Fern{\'a}ndez and Derek K. Jones}
}
@article {914,
	title = {Q-space quantitative diffusion MRI measures using a stretched-exponential representation},
	journal = {arXiv},
	year = {2020},
	url = {https://arxiv.org/abs/2009.07376},
	author = {Tomasz Pieciak and Maryam Afzali and Fabian Bogusz and Santiago Aja-Fern{\'a}ndez and Derek K. Jones}
}
