Arterial Spin Labeling Perfusion MRI Signal Processing Through Traditional Methods and Machine Learning

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참고문헌 (73)

1. Detre JA, "Perfusion imaging", Magn Reson Med, 23, pp.37~45 (1992)
2. Williams DS, "Magnetic resonance imaging of perfusion using spin inversion of arterial water", Proc Natl Acad Sci U S A, 89, pp.212~216 (1992)
3. Wong EC, "Functional MRI", pp.63~69 (1999), Springer
4. Ye FQ, "H215O PET validation of steady-state arterial spin tagging cerebral blood flow measurements in humans", Magn Reson Med, 44, pp.450~456 (2000)
5. Wang Z, "Characterizing early Alzheimer’s disease and disease progression using hippocampal volume and arterial spin labeling perfusion MRI", J Alzheimers Dis, 42(Suppl 4), pp.S495~S502 (2014)
6. Wang Z, "Arterial spin labeled MRI in prodromal Alzheimer’s disease : a multi-site study", Neuroimage Clin, 2, pp.630~636 (2013)
7. Chui CK, "An introduction to wavelets" (1992), Academic Press
8. Huang NE, "A review on Hilbert-Huang transform : method and its applications to geophysical studies", Rev Geophys, 46, pp.RG2006~ (2008)
9. Aguirre GK, "Experimental design and the relative sensitivity of BOLD and perfusion fMRI", Neuroimage, 15, pp.488~500 (2002)
10. Wang J, "To smooth or not to smooth? ROC analysis of perfusion fMRI data", Magn Reson Imaging, 23, pp.75~81 (2005)
11. Wang Z, "Boost up the detection sensitivity of ASL perfusion fMRI through support vector machine", Proceedings of the 2006 International Conference of the IEEE Engineering in Medicine and Biology Society, pp.1006~1009 (2006), IEEE
12. Wang Z, "Support vector machine learning-based fMRI data group analysis", Neuroimage, 36, pp.1139~1151 (2007)
13. Wang Z, "Empirical optimization of ASL data analysis using an ASL data processing toolbox : ASLtbx", Magn Reson Imaging, 26, pp.261~269 (2008)
14. Liu TT, "A signal processing model for arterial spin labeling functional MRI", Neuroimage, 24, pp.207~215 (2005)
15. Lu H, "Detrimental effects of BOLD signal in arterial spin labeling fMRI at high field strength", Magn Reson Med, 56, pp.546~552 (2006)
16. Mumford JA, "Estimation efficiency and statistical power in arterial spin labeling fMRI", Neuroimage, 33, pp.103~114 (2006)
17. Restom K, "Physiological noise reduction for arterial spin labeling functional MRI", Neuroimage, 31, pp.1104~1115 (2006)
18. Tan H, "A fast, effective filtering method for improving clinical pulsed arterial spin labeling MRI", J Magn Reson Imaging, 29, pp.1134~1139 (2009)
19. Bibic A, "Denoising of arterial spin labeling data: wavelet-domain filtering compared with Gaussian smoothing", MAGMA, 23, pp.125~137 (2010)
20. Wells JA, "Reduction of errors in ASL cerebral perfusion and arterial transit time maps using image de-noising", Magn Reson Med, 64, pp.715~724 (2010)
21. Wang Z, "CBF quantification using a data derived arterial spin labeling temporal profile", CSMRM & OCSMRM Joint Meeting 2010and ESMRMB Workshop (2010)
22. Wang Z, "Regional coherence-based denoising (RECODE)for arterial spin labeled perfusion MRI", Proceedings of the 19th Annual ISMRM Scientific Meeting and Exhibition, pp.3970~ (2011), ISMRM
23. Wang Z, "Improving cerebral blood flow quantification for arterial spin labeled perfusion MRI by removing residual motion artifacts and global signal fluctuations", Magn Reson Imaging, 30, pp.1409~1415 (2012)
24. Wang Z, "Support vector machine learning-based cerebral blood flow quantification for arterial spin labeling MRI", Hum Brain Mapp, 35, pp.2869~2875 (2014)
25. Dolui S, "Structural correlation-based outlier rejection(SCORE)algorithm for arterial spin labeling time series", J Magn Reson Imaging, 45, pp.1786~1797 (2016)
26. Wang Z, "Priors-guided adaptive outlier cleaning for arterial spin labeling perfusion MRI", Proceedings of the 24th Annual Meeting & Exhibition (2016), ISMRM
27. Zhu H, "Patch-based local learning method for cerebral blood flow quantification with arterial spin-labeling MRI", Med Biol Eng Comput, 56, pp.951~956 (2018)
28. Zhu H, "Arterial spin labeling perfusion MRI signal denoising using robust principal component analysis", J Neurosci Methods, 295, pp.10~19 (2018)
29. Spann SM, "Spatio-temporal TGV denoising for ASL perfusion imaging", Neuroimage, 157, pp.81~96 (2017)
30. Chappell MA, "Variational Bayesian inference for a nonlinear forward model", IEEE Trans Signal Process, 57, pp.223~236 (2008)
31. Hernandez-Garcia L, "Recent technical developments in ASL: a review of the state of the art", Magn Reson Med, 88, pp.2021~2042 (2022)
32. Dai W, "Continuous flowdriven inversion for arterial spin labeling using pulsed radio frequency and gradient fields", Magn Reson Med, 60, pp.1488~1497 (2008)
33. Alsop DC, "Recommended implementation of arterial spin-labeled perfusion MRI for clinical applications : a consensus of the ISMRM perfusion study group and the European consortium for ASL in dementia", Magn Reson Med, 73, pp.102~116 (2015)
34. Qin Q, "Velocity-selective arterial spin labeling perfusion MRI : a review of the state of the art and recommendations for clinical implementation", Magn Reson Med, 88, pp.1528~1547 (2022)
35. Luh WM, "QUIPSS II with thinslice TI1 periodic saturation : a method for improving accuracy of quantitative perfusion imaging using pulsed arterial spin labeling", Magn Reson Med, 41, pp.1246~1254 (1999)
36. Wong EC, "Implementation of quantitative perfusion imaging techniques for functional brain mapping using pulsed arterial spin labeling", NMR Biomed, 10, pp.237~249 (1997)
37. Vidorreta M, "Effects of readout sequence on the temporal and spatial SNR of pseudo-continuous arterial spin labeling", Proceedings of the 20th Annual Meeting & Exhibition (2012)
38. Vidorreta M, "Comparison of 2D and 3D single-shot ASL perfusion fMRI sequences", Neuroimage, 66, pp.662~671 (2012)
39. Fernández-Seara MA, "Continuous arterial spin labeling perfusion measurements using single shot 3D GRASE at 3 T", Magn Reson Med, 54, pp.1241~1247 (2005)
40. Wang DJ, "Multi-delay multi-parametric arterial spin-labeled perfusion MRI in acute ischemic stroke —Comparison with dynamic susceptibility contrast enhanced perfusion imaging", Neuroimage Clin, 3, pp.1~7 (2013)
41. Feinberg DA, "Multiplexed echo planar imaging for sub-second whole brain FMRI and fast diffusion imaging", PLoS One, 5, pp.e15710~ (2010)
42. Setsompop K, "Blipped-controlled aliasing in parallel imaging for simultaneous multislice echo planar imaging with reduced g-factor penalty", Magn Reson Med, 67, pp.1210~1224 (2012)
43. Buxton RB, "A general kinetic model for quantitative perfusion imaging with arterial spin labeling", Magn Reson Med, 40, pp.383~396 (1998)
44. Wells JA, "In vivo Hadamard encoded continuous arterial spin labeling(HCASL)", Magn Reson Med, 63, pp.1111~1118 (2010)
45. Dai W, "Volumetric measurement of perfusion and arterial transit delay using hadamard encoded continuous arterial spin labeling", Magn Reson Med, 69, pp.1014~1022 (2013)
46. Friston KJ, "Spatial registration and normalization of images", Hum Brain Mapp, 3, pp.165~189 (1995)
47. Friston KJ, "Movement-related effects in fMRI time-series", Magn Reson Med, 35, pp.346~355 (1996)
48. Behzadi Y, "A component based noise correction method(CompCor)for BOLD and perfusion based fMRI", Neuroimage, 37, pp.90~101 (2007)
49. Avants BB, "Robust cerebral blood flow reconstruction from perfusion imaging with an open-source, multi-platform toolkit", Proceedings of Perfusion MRI: Standardization, Beyond CBF and Everyday Clinical Applications, 2012, pp.21~ (2012), ISMRM
50. Maumet C, "Robust estimation of the cerebral blood flow in arterial spin labelling", Magn Reson Imaging, 32, pp.497~504 (2014)
51. Li Y, "Priors-guided slice-wise adaptive outlier cleaning for arterial spin labeling perfusion MRI", J Neurosci Methods, 307, pp.248~253 (2018)
52. Leenders KL, "Cerebral blood flow, blood volume and oxygen utilization. Normal values and effect of age", Brain, 113(Pt 1), pp.27~47 (1990)
53. Du AT, "Hypoperfusion in frontotemporal dementia and Alzheimer disease by arterial spin labeling MRI", Neurology, 67, pp.1215~1220 (2006)
54. Asllani I, "Regression algorithm correcting for partial volume effects in arterial spin labeling MRI", Magn Reson Med, 60, pp.1362~1371 (2008)
55. Chen JJ, "Age-associated reductions in cerebral blood flow are independent from regional atrophy", Neuroimage, 55, pp.468~478 (2011)
56. Hu WT, "Distinct cerebral perfusion patterns in FTLD and AD", Neurology, 75, pp.881~888 (2010)
57. Carone D, "ICA-based denoising for ASL perfusion imaging", Neuroimage, 200, pp.363~372 (2019)
58. Wang Z, "Improving ASL perfusion MRI-based functional connectivity analysis with robust principal component analysis", Proceedings of the 24th Annual Meeting & Exhibition, 2016, pp.2873~ (2016), ISMRM
59. Gong E, "Boosting SNR and", or resolution of arterial spin label (ASL) imaging using multi-contrast approaches with multi-lateral guided filter and deep networks, 2017, ~[DOI]
60. Liu Q, "Increasing arterial spin labeling perfusion image resolution using convolutional neural networks with residual-learning", Proceedings of the Joint Annual Meeting ISMRMESMRMB (2018)
61. Li Z, "A two-stage multi-loss super-resolution network for arterial spin labeling magnetic resonance imaging", Medical Image Computing and Computer Assisted Intervention – MICCAI 2019, pp.12~20 (2019), Springer
62. Kim KH, "Improving arterial spin labeling by using deep learning", Radiology, 287, pp.658~666 (2018)
63. Xie D, "Denoising arterial spin labeling perfusion MRI with deep machine learning", Magn Reson Imaging, 68, pp.95~105 (2020)
64. Xie D, "Denoising arterial spin labeling cerebral blood flow images using deep learning-based methods", Proceedings of the ISMRM Workshop on Machine Learning (2018), ISMRM
65. Xie D, "Super-ASL: improving SNR and temporal resolution of ASL MRI using deep learning", Proceedings of the ISMRM Workshop on Machine Learning (2018), ISMRM
66. Xie D, "A learning-fromnoise dilated wide activation network for denoising arterial spin labeling (ASL) perfusion images", arXiv, ~ (2020)
67. Zhang L, "Improving sensitivity of arterial spin labeling perfusion MRI in Alzheimer’s disease using transfer learning of deep learning-based ASL denoising", J Magn Reson Imaging, 55, pp.1710~1722 (2022)
68. Hales PW, "Combined denoising and suppression of transient artifacts in arterial spin labeling MRI using deep learning", J Magn Reson Imaging, 52, pp.1413~1426 (2020)
69. Kim D, "Parametric ATT and CBF mapping using a three-dimensional convolutional neural network", Proceedings of Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting (2022), ISMRM
70. Li Y, "Acceleration of cerebral blood flow and arterial transit time maps estimation from multiple post-labeling delay arterial spin-labeled MRI via deep learning", arXiv, ~ (2022)
71. Zaharchuk G, "Deep learning in neuroradiology", AJNR Am J Neuroradiol, 39, pp.1776~1784 (2018)
72. Xie D, "BOLD fMRI-based brain perfusion prediction using deep dilated wide activation networks", International Workshop on Machine Learning in Medical Imaging, pp.373~381 (2019), Springer
73. Xie D, "Estimating cerebral blood flow from BOLD signal using deep dilated wide activation networks", Proceedings of the 2020 ISMRM & SMRT Virtual Conference & Exhibition (2020), ISMRM

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