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	doi = {10.1002/mrm.1910290212},
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}

@article{fang_submillimeter_nodate,
	title = {Submillimeter {MR} fingerprinting using deep learning–based tissue quantification},
	volume = {84},
	copyright = {© 2019 International Society for Magnetic Resonance in Medicine},
	issn = {1522-2594},
	url_ = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.28136},
	doi = {10.1002/mrm.28136},
	language = {en},
	urldate = {2020-01-20},
	journal = {Magnetic Resonance in Medicine},
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	year = {2020},
	pages = {579– 591},
	keywords = {quantitative imaging, MR fingerprinting, deep learning, pediatric imaging},
}

@inproceedings{balsiger_spatial_2019,
	address = {London, United Kingdom},
	series = {Proceedings of {Machine} {Learning} {Research}},
	title = {On the {Spatial} and {Temporal} {Influence} for the {Reconstruction} of {Magnetic} {Resonance} {Fingerprinting}},
	volume = {102},
	url_ = {http://proceedings.mlr.press/v102/balsiger19a.html},
	booktitle = {Proceedings of {The} 2nd {International} {Conference} on {Medical} {Imaging} with {Deep} {Learning}},
	publisher = {PMLR},
	author = {Balsiger, Fabian and Scheidegger, Olivier and Carlier, Pierre G. and Marty, Benjamin and Reyes, Mauricio},
	editor = {Cardoso, M. Jorge and Feragen, Aasa and Glocker, Ben and Konukoglu, Ender and Oguz, Ipek and Unal, Gozde and Vercauteren, Tom},
	month = jul,
	year = {2019},
	keywords = {Magnetic Resonance Imaging, Humans, Female, Algorithms, Image Enhancement, Image Interpretation, Computer-Assisted, Reproducibility of Results, Sensitivity and Specificity, Signal Processing, Computer-Assisted, Adult, Brain, Male, Phantoms, Imaging},
	pages = {27--38}
}

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	volume = {74},
	issn = {1522-2594},
	doi = {10.1002/mrm.25559},
	language = {eng},
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	month = dec,
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	keywords = {Magnetic Resonance Imaging, Humans, Algorithms, Image Enhancement, Image Interpretation, Computer-Assisted, Reproducibility of Results, Sensitivity and Specificity, Signal Processing, Computer-Assisted, Brain, quantitative imaging, FISP, MR fingerprinting, Phantoms, Imaging, relaxation time, spiral},
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}

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}

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	issn = {0740-3194},
	language = {eng},
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}

@article{deoni_rapid_2003,
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	language = {eng},
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@inproceedings{jiang_simultaneous_2016,
	address = {Singapore},
	title = {Simultaneous {Quantification} of {T1}, {T2} and {Diffusion} with {Diffusion}-weighted drive-equilibrium prepared {Magnetic} {Resonance} {Fingerprinting}},
	urldate = {2018-02-21},
	booktitle = {Proceedings of the 24th {Annual} {Meeting} of {International} {Society} for {Magnetic} {Resonance} in {Medicine} ({ISMRM})},
	author = {Jiang, Yun and Hamilton, Jesse Ian and Wright, Katharine L. and Ma, Dan and Seiberlich, Nicole and Gulani, Vikas and Griswold, Mark A.},
	year = {2016},
}

@inproceedings{jiang_simultaneous_2017,
	address = {Honolulu, HI, USA},
	title = {Simultaneous {T1}, {T2} and {Diffusion} {Quantification} using {Multiple} {Contrast} {Prepared} {Magnetic} {Resonance} {Fingerprinting}},
	urldate = {2018-02-21},
	booktitle = {Proceedings of the 25th {Annual} {Meeting} of {International} {Society} for {Magnetic} {Resonance} in {Medicine} ({ISMRM})},
	author = {Jiang, Yun and Hamilton, Jesse Ian and Lo, Wei-Ching and Wright, Katharine L. and Ma, Dan and Coristine, Andrew J. and Seiberlich, Nicole and Gulani, Vikas and Griswold, Mark A.},
	year = {2017},
}

@article{ma_magnetic_2013,
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}

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@inproceedings{tanno_bayesian_2017,
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	booktitle = {20th {International} {Conference} on {Medical} {Image} {Computing} and {Computer} {Assisted} {Intervention} ({MICCAI})},
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	year = {2017}
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@inproceedings{jiang_simultaneous_2014,
	address = {Milan, Italy},
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	booktitle = {Proceedings of the 22nd {Annual} {Meeting} of {International} {Society} for {Magnetic} {Resonance} in {Medicine} ({ISMRM})},
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	year = {2014}
}

@article{weigel_extended_2010,
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	doi = {10.1016/j.jmr.2010.05.011},
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@article{thust_glioma_2018,
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@inproceedings{rieger_simultaneous_2018,
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	booktitle = {Proceedings of the 26th {Annual} {Meeting} of {International} {Society} for {Magnetic} {Resonance} in {Medicine} ({ISMRM})},
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@inproceedings{leemans_exploredti_2009,
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	booktitle = {Proceedings of the 17th {Annual} {Meeting} of {International} {Society} for {Magnetic} {Resonance} in {Medicine} ({ISMRM})},
	author = {Leemans, Alexander and Jeurissen, Ben and Sijbers, Jan and Jones, Derek K.},
	year = {2009},
	keywords = {Phantoms, Imaging, Distortion, Adobe Streamline, Cambridge Structural Database, Cuboid, Deconvolution, DICOM, Diffusion Tensor Imaging, Glyph, Gradient, Graphical user interface, Image map, Linear least squares (mathematics), MATLAB, Modality (human–computer interaction), Non-linear least squares, Preprocessor, Screenshot, Snapshot isolation, Transverse wave, Unix, Usability, Video card, Voxel, width}
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}

@inproceedings{golbabaee_geometry_2019,
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	doi = {10.1109/ICASSP.2019.8683549},
	booktitle = {{ICASSP} 2019 - 2019 {IEEE} {International} {Conference} on {Acoustics}, {Speech} and {Signal} {Processing} ({ICASSP})},
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	month = may,
	year = {2019},
	note = {ISSN: 1520-6149},
	keywords = {affine regression, approximation theory, biomedical MRI, Bloch response manifold projection, deep learning, deep learning approach, dictionary, dictionary-matching step, DM baseline, fine-grid manifold enumeration, fingerprint dictionaries, image filtering, image matching, image reconstruction, image segmentation, inverse problem, learning (artificial intelligence), magnetic resonance fingerprinting, Magnetic resonance fingerprinting, manifold compressed sensing, matched-filters, medical image processing, MRF dictionary, MRF-Net, multiparametric quantitative MRI applications, NMR characteristics, piece-wise affine approximation, regression analysis},
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	urldate = {2019-02-26},
	booktitle = {Proceedings of the 26th {Annual} {Meeting} of {International} {Society} for {Magnetic} {Resonance} in {Medicine} ({ISMRM})},
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@article{fang_deep_2019,
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	number={10},
	pages={2364-2374},
	keywords={biological tissues;biomedical MRI;brain;feature extraction;image sampling;learning (artificial intelligence);medical image processing;phantoms;undersampled MRF data;final tissue property map;extracted feature maps;spatially constrained quantification module;high-dimensional signal evolution;low-dimensional feature vector;feature extraction module;deep learning model;central pixel;multiple neighboring pixels;spatially constrained quantification method;estimate tissue properties;MRF signal evolution;sampling data;tissue quantification method;MRF acquisition;human body;multiple important tissue properties;quantitative imaging technique;magnetic resonance fingerprinting;spatially constrained tissue quantification;Imaging;Feature extraction;Dictionaries;Deep learning;Mathematical model;Acceleration;Learning systems;Magnetic resonance fingerprinting;neural network;quantitative magnetic resonance imaging;tissue quantification},
	doi={10.1109/TMI.2019.2899328},
	ISSN={1558-254X},
	month={Oct}
}

@article{avants_reproducible_2011,
	title = {A {Reproducible} {Evaluation} of {ANTs} {Similarity} {Metric} {Performance} in {Brain} {Image} {Registration}},
	volume = {54},
	issn = {1053-8119},
	doi = {10.1016/j.neuroimage.2010.09.025},
	number = {3},
	urldate = {2020-04-15},
	journal = {NeuroImage},
	author = {Avants, Brian B. and Tustison, Nicholas J. and Song, Gang and Cook, Philip A. and Klein, Arno and Gee, James C.},
	month = feb,
	year = {2011},
	pmid = {20851191},
	pmcid = {PMC3065962},
	pages = {2033--2044},
}