Submillimeter MR fingerprinting using deep learning–based tissue quantification

To develop a rapid 2D MR fingerprinting technique with a submillimeter in‐plane resolution using a deep learning–based tissue quantification approach.

[1]  Yun Fu,et al.  Image Super-Resolution Using Very Deep Residual Channel Attention Networks , 2018, ECCV.

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

[3]  Bo Zhu,et al.  MR fingerprinting Deep RecOnstruction NEtwork (DRONE) , 2017, Magnetic resonance in medicine.

[4]  F. Knoll,et al.  Low rank alternating direction method of multipliers reconstruction for MR fingerprinting , 2016, Magnetic resonance in medicine.

[5]  Qian Wang,et al.  Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting , 2019, IEEE Transactions on Medical Imaging.

[6]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[7]  Vikas Gulani,et al.  Investigating and reducing the effects of confounding factors for robust T1 and T2 mapping with cardiac MR fingerprinting. , 2018, Magnetic resonance imaging.

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

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

[10]  Li Feng,et al.  MANTIS: Model‐Augmented Neural neTwork with Incoherent k‐space Sampling for efficient MR parameter mapping , 2019, Magnetic resonance in medicine.

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

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

[13]  Yun Jiang,et al.  Improved magnetic resonance fingerprinting reconstruction with low‐rank and subspace modeling , 2018, Magnetic resonance in medicine.

[14]  Soonmee Cha,et al.  Quantitative apparent diffusion coefficients and T2 relaxation times in characterizing contrast enhancing brain tumors and regions of peritumoral edema , 2005, Journal of magnetic resonance imaging : JMRI.

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

[16]  Andreas K. Maier,et al.  Deep Learning for Magnetic Resonance Fingerprinting: A New Approach for Predicting Quantitative Parameter Values from Time Series , 2017, GMDS.

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

[18]  Yonina C. Eldar,et al.  Low rank magnetic resonance fingerprinting , 2016, 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[19]  Ze Wang,et al.  Magnetic Resonance Fingerprinting Using a Fast Dictionary Searching Algorithm: MRF-ZOOM , 2019, IEEE Transactions on Biomedical Engineering.

[20]  Olivier Scheidegger,et al.  On the Spatial and Temporal Influence for the Reconstruction of Magnetic Resonance Fingerprinting , 2019, MIDL.

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

[22]  Peter Jezzard,et al.  Rapid T1 mapping using multislice echo planar imaging , 2001, Magnetic resonance in medicine.

[23]  P. Lundberg,et al.  Quantitative MRI for Analysis of Active Multiple Sclerosis Lesions without Gadolinium-Based Contrast Agent , 2016, American Journal of Neuroradiology.

[24]  Dongdong Chen,et al.  Geometry of Deep Learning for Magnetic Resonance Fingerprinting , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[25]  Sairam Geethanath,et al.  Magnetic Resonance Fingerprinting Reconstruction via Spatiotemporal Convolutional Neural Networks , 2018, MLMIR@MICCAI.

[26]  R. Brooks,et al.  T1 and T2 in the brain of healthy subjects, patients with Parkinson disease, and patients with multiple system atrophy: relation to iron content. , 1999, Radiology.

[27]  Yonina C. Eldar,et al.  Magnetic Resonance Fingerprinting Using a Residual Convolutional Neural Network , 2019, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[28]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[29]  Qing Li,et al.  Fast 3D brain MR fingerprinting based on multi‐axis spiral projection trajectory , 2019, Magnetic resonance in medicine.

[30]  Vikas Gulani,et al.  Fast 3D magnetic resonance fingerprinting for a whole‐brain coverage , 2018, Magnetic resonance in medicine.

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

[32]  Josef Pfeuffer,et al.  AIR-MRF: Accelerated iterative reconstruction for magnetic resonance fingerprinting. , 2017, Magnetic resonance imaging.

[33]  Felix Breuer,et al.  Simultaneous multislice (SMS) imaging techniques , 2015, Magnetic resonance in medicine.