MR fingerprinting Deep RecOnstruction NEtwork (DRONE)

Demonstrate a novel fast method for reconstruction of multi‐dimensional MR fingerprinting (MRF) data using deep learning methods.

[1]  Yoshua Bengio,et al.  Extracting and composing robust features with denoising autoencoders , 2008, ICML '08.

[2]  Jürgen Schmidhuber,et al.  Deep learning in neural networks: An overview , 2014, Neural Networks.

[3]  M. Griswold,et al.  MR fingerprinting using fast imaging with steady state precession (FISP) with spiral readout , 2015, Magnetic resonance in medicine.

[4]  Jianhui Zhong,et al.  Robust sliding‐window reconstruction for Accelerating the acquisition of MR fingerprinting , 2017, Magnetic resonance in medicine.

[5]  J. Duerk,et al.  Magnetic Resonance Fingerprinting , 2013, Nature.

[6]  Hanzhang Lu,et al.  Multiparametric estimation of brain hemodynamics with MR fingerprinting ASL , 2017, Magnetic resonance in medicine.

[7]  Sepp Hochreiter,et al.  The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions , 1998, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[8]  Yoshua Bengio,et al.  Gradient Flow in Recurrent Nets: the Difficulty of Learning Long-Term Dependencies , 2001 .

[9]  M. McMahon,et al.  Rapid and quantitative chemical exchange saturation transfer (CEST) imaging with magnetic resonance fingerprinting (MRF) , 2017, Magnetic resonance in medicine.

[10]  Debra F. McGivney,et al.  Slice profile and B1 corrections in 2D magnetic resonance fingerprinting , 2017, Magnetic resonance in medicine.

[11]  Stephen C. Hora Goodness of fit tests using regression , 1985 .

[12]  M. Griswold,et al.  Inversion recovery TrueFISP: Quantification of T1, T2, and spin density , 2004, Magnetic resonance in medicine.

[13]  Yun Jiang,et al.  SVD Compression for Magnetic Resonance Fingerprinting in the Time Domain , 2014, IEEE Transactions on Medical Imaging.

[14]  Robin M Heidemann,et al.  Generalized autocalibrating partially parallel acquisitions (GRAPPA) , 2002, Magnetic resonance in medicine.

[15]  Ouri Cohen,et al.  Algorithm comparison for schedule optimization in MR fingerprinting. , 2017, Magnetic resonance imaging.

[16]  Martín Abadi,et al.  TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems , 2016, ArXiv.

[17]  Kurt Hornik,et al.  Multilayer feedforward networks are universal approximators , 1989, Neural Networks.

[18]  T. Peters,et al.  High‐resolution T1 and T2 mapping of the brain in a clinically acceptable time with DESPOT1 and DESPOT2 , 2005, Magnetic resonance in medicine.

[19]  A. V. Olgac,et al.  Performance Analysis of Various Activation Functions in Generalized MLP Architectures of Neural Networks , 2011 .

[20]  J. Lawless,et al.  A simulation study of ridge and other regression estimators , 1976 .

[21]  Yong Chen,et al.  Multiscale reconstruction for MR fingerprinting , 2016, Magnetic resonance in medicine.

[22]  Kawin Setsompop,et al.  Fast group matching for MR fingerprinting reconstruction , 2015, Magnetic resonance in medicine.

[23]  Ouri Cohen,et al.  Optimized inversion‐time schedules for quantitative T1 measurements based on high‐resolution multi‐inversion EPI , 2017, Magnetic resonance in medicine.

[24]  Kawin Setsompop,et al.  Accelerating magnetic resonance fingerprinting (MRF) using t‐blipped simultaneous multislice (SMS) acquisition , 2016, Magnetic resonance in medicine.

[25]  G Nair,et al.  Transverse relaxation of cerebrospinal fluid depends on glucose concentration. , 2017, Magnetic resonance imaging.

[26]  Sebastian Weingärtner,et al.  Magnetic resonance fingerprinting using echo‐planar imaging: Joint quantification of T1 and T2∗ relaxation times , 2017, Magnetic resonance in medicine.

[27]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[28]  Lawrence L. Wald,et al.  3D MR fingerprinting with accelerated stack-of-spirals and hybrid sliding-window and GRAPPA reconstruction , 2017, NeuroImage.

[29]  Peng Hu,et al.  Comparison of T1 measurement using ISMRM/NIST system phantom | NIST , 2016 .

[30]  D. Louis Collins,et al.  Design and construction of a realistic digital brain phantom , 1998, IEEE Transactions on Medical Imaging.

[31]  Matthias Weigel,et al.  Extended phase graphs: Dephasing, RF pulses, and echoes ‐ pure and simple , 2015, Journal of magnetic resonance imaging : JMRI.

[32]  Nicole Seiberlich,et al.  Low rank approximation methods for MR fingerprinting with large scale dictionaries , 2018, Magnetic resonance in medicine.

[33]  Stella X. Yu,et al.  Better than real: Complex-valued neural nets for MRI fingerprinting , 2017, 2017 IEEE International Conference on Image Processing (ICIP).

[34]  M. Griswold,et al.  Repeatability of magnetic resonance fingerprinting T1 and T2 estimates assessed using the ISMRM/NIST MRI system phantom , 2017, Magnetic resonance in medicine.