1 |
Schmierer K, Tozer DJ, Scaravilli F, et al. Quantitative magnetization transfer imaging in postmortem multiple sclerosis brain. J Magn Reson Imaging 2007;26:41-51
DOI
|
2 |
Garcia M, Gloor M, Bieri O, et al. Imaging of primary brain tumors and metastases with fast quantitative 3-dimensional magnetization transfer. J Neuroimaging 2015;25:1007-1014
DOI
|
3 |
Kim KH, Choi SH, Park SH. Feasibility of quantifying arterial cerebral blood volume using multiphase alternate ascending/descending directional navigation (ALADDIN). PLoS One 2016;11:e0156687
DOI
|
4 |
Luu HM, Kim DH, Kim JW, Choi SH, Park SH. qMTNet: accelerated quantitative magnetization transfer imaging with artificial neural networks. Magn Reson Med 2020;85:298-308
DOI
|
5 |
Karras T, Laine S, Aittala M, et al. Analyzing and improving the image quality of StyleGAN. Proc IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020:8110-8119
|
6 |
Henkelman RM, Huang X, Xiang QS, Stanisz GJ, Swanson SD, Bronskill MJ. Quantitative interpretation of magnetization transfer. Magn Reson Med 1993;29:759-766
DOI
|
7 |
Park SH, Duong TQ. Alternate ascending/descending directional navigation approach for imaging magnetization transfer asymmetry. Magn Reson Med 2011;65:1702-1710
DOI
|
8 |
He K, Zhang X, Ren S, Sun J. Deep residual learning for image recognition. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016:770-778
|
9 |
Park H, Lee J, Park SH, Choi SH. Evaluation of tumor blood flow using alternate ascending/descending directional navigation in primary brain tumors: a comparison study with dynamic susceptibility contrast magnetic resonance imaging. Korean J Radiol 2019;20:275-282
DOI
|
10 |
Park SH, Zhao T, Kim JH, Boada FE, Bae KT. Suppression of effects of gradient imperfections on imaging with alternate ascending/descending directional navigation. Magn Reson Med 2012;68:1600-1606
DOI
|
11 |
Kingma DP, Ba J. Adam: a method for stochastic optimization. Proc 3rd International Conference on Learning Representations (ICLR), 2015
|
12 |
Abadi M, Barham P, Chen J, et al. TensorFlow: a system for large-scale machine learning. Proc the OSDI'16: 12th USENIX Symposium on Operating Systems Design and Implementation; Savannah, GA, USA: USENIX Association; 2016:265-283
|
13 |
Srivastava N, Hinton GE, Krizhevsky A, Sutskever I, Salakhutdinov R. Dropout: a simple way to prevent neural networks from overfitting. J Mach Learn Res 2014;15:1929-1958
|
14 |
Wilcoxon F. Individual comparisons by ranking methods. Biometrics 1945;1:80-83
DOI
|
15 |
Cohen O, Zhu B, Rosen MS. MR fingerprinting deep reconstruction network (DRONE). Magn Reson Med 2018;80:885-894
DOI
|
16 |
Lee D, Yoo J, Tak S, Ye JC. Deep residual learning for accelerated MRI using magnitude and phase networks. IEEE Trans Biomed Eng 2018;65:1985-1995
DOI
|
17 |
McLean MA. Accelerated quantitative magnetization transfer (qMT) imaging (unpublished master's thesis). University of Calgary, Calgary, AB, 2018:94
|
18 |
Goodfellow I, Pouget-Abadie J, Mirza M, et al. Generative adversarial nets. Advances in Neural Information Processing Systems, 2014:2672-2680
|
19 |
Jung W, Yoon J, Choi JY, et al. Exploring linearity of deep neural network trained QSM: QSMnet+. arXiv preprint arXiv:1909.07716, 2019
|
20 |
Cercignani M, Alexander DC. Optimal acquisition schemes for in vivo quantitative magnetization transfer MRI. Magn Reson Med 2006;56:803-810
DOI
|
21 |
Gochberg DF, Gore JC. Quantitative magnetization transfer imaging via selective inversion recovery with short repetition times. Magn Reson Med 2007;57:437-441
DOI
|
22 |
Dortch RD, Li K, Gochberg DF, et al. Quantitative magnetization transfer imaging in human brain at 3 T via selective inversion recovery. Magn Reson Med 2011;66:1346-1352
DOI
|
23 |
Chen LC, Papandreou G, Kokkinos I, Murphy K, Yuille AL. DeepLab: semantic image segmentation with deep convolutional nets, atrous convolution, and fully connected CRFs. IEEE Trans Pattern Anal Mach Intell 2018;40:834-848
DOI
|
24 |
Caruana R. Multitask learning. Machine Learning 1997;28:41-75
DOI
|
25 |
Lee J, Lee D, Choi JY, Shin D, Shin HG, Lee J. Artificial neural network for myelin water imaging. Magn Reson Med 2020;83:1875-1883
DOI
|
26 |
Yoon J, Gong E, Chatnuntawech I, et al. Quantitative susceptibility mapping using deep neural network: QSMnet. Neuroimage 2018;179:199-206
DOI
|
27 |
Johnson J, Alahi A, Fei-Fei L. Perceptual losses for realtime style transfer and super-resolution. Proc European Conference on Computer Vision, 2016:694-711
|
28 |
Lee D, Yoo J, Ye JC. Deep residual learning for compressed sensing MRI. IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017), 2017:15-18
|
29 |
Heule R, Bause J, Pusterla O, Scheffler K. Multi-parametric artificial neural network fitting of phase-cycled balanced steady-state free precession data. Magn Reson Med 2020;84:2981-2993
DOI
|
30 |
Cabana J-F, Gu Y, Boudreau M, et al. Quantitative magnetization transfer imaging made easy with qMTLab: software for data simulation, analysis, and visualization. Concepts Magn Reson 2015;44A:263-277
DOI
|
31 |
Gochberg DF, Gore JC. Quantitative imaging of magnetization transfer using an inversion recovery sequence. Magn Reson Med 2003;49:501-505
DOI
|
32 |
Li K, Zu Z, Xu J, et al. Optimized inversion recovery sequences for quantitative T1 and magnetization transfer imaging. Magn Reson Med 2010;64:491-500
DOI
|
33 |
Kim JW, Lee SL, Choi SH, Park SH. Rapid framework for quantitative magnetization transfer imaging with interslice magnetization transfer and dictionary-driven fitting approaches. Magn Reson Med 2019;82:1671-1683
DOI
|
34 |
Han PK, Barker JW, Kim KH, Choi SH, Bae KT, Park SH. Inter-slice blood flow and magnetization transfer effects as a new simultaneous imaging strategy. PLoS One 2015;10:e0140560
DOI
|
35 |
Park SH, Duong TQ. Brain MR perfusion-weighted imaging with alternate ascending/descending directional navigation. Magn Reson Med 2011;65:1578-1591
DOI
|
36 |
Harrison NA, Cooper E, Dowell NG, et al. Quantitative magnetization transfer imaging as a biomarker for effects of systemic inflammation on the brain. Biol Psychiatry 2015;78:49-57
DOI
|
37 |
Barker JW, Han PK, Choi SH, Bae KT, Park SH. Investigation of inter-slice magnetization transfer effects as a new method for MTR imaging of the human brain. PLoS One 2015;10:e0117101
DOI
|
38 |
Levesque IR, Giacomini PS, Narayanan S, et al. Quantitative magnetization transfer and myelin water imaging of the evolution of acute multiple sclerosis lesions. Magn Reson Med 2010;63:633-640
DOI
|