312 related articles for article (PubMed ID: 31377323)
21. STrategically Acquired Gradient Echo (STAGE) imaging, part I: Creating enhanced T1 contrast and standardized susceptibility weighted imaging and quantitative susceptibility mapping.
Chen Y; Liu S; Wang Y; Kang Y; Haacke EM
Magn Reson Imaging; 2018 Feb; 46():130-139. PubMed ID: 29056394
[TBL] [Abstract][Full Text] [Related]
22. QQ-NET - using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping.
Cho J; Zhang J; Spincemaille P; Zhang H; Hubertus S; Wen Y; Jafari R; Zhang S; Nguyen TD; Dimov AV; Gupta A; Wang Y
Magn Reson Med; 2022 Mar; 87(3):1583-1594. PubMed ID: 34719059
[TBL] [Abstract][Full Text] [Related]
23. Deep learning-regularized, single-step quantitative susceptibility mapping quantification.
Wang Z; Mak HK; Cao P
NMR Biomed; 2023 Mar; 36(3):e4849. PubMed ID: 36259729
[TBL] [Abstract][Full Text] [Related]
24. Fast quantitative susceptibility mapping using 3D EPI and total generalized variation.
Langkammer C; Bredies K; Poser BA; Barth M; Reishofer G; Fan AP; Bilgic B; Fazekas F; Mainero C; Ropele S
Neuroimage; 2015 May; 111():622-30. PubMed ID: 25731991
[TBL] [Abstract][Full Text] [Related]
25. DeepQSM - using deep learning to solve the dipole inversion for quantitative susceptibility mapping.
Bollmann S; Rasmussen KGB; Kristensen M; Blendal RG; Østergaard LR; Plocharski M; O'Brien K; Langkammer C; Janke A; Barth M
Neuroimage; 2019 Jul; 195():373-383. PubMed ID: 30935908
[TBL] [Abstract][Full Text] [Related]
26. Rapid two-step dipole inversion for susceptibility mapping with sparsity priors.
Kames C; Wiggermann V; Rauscher A
Neuroimage; 2018 Feb; 167():276-283. PubMed ID: 29138089
[TBL] [Abstract][Full Text] [Related]
27. Single-step quantitative susceptibility mapping with variational penalties.
Chatnuntawech I; McDaniel P; Cauley SF; Gagoski BA; Langkammer C; Martin A; Grant PE; Wald LL; Setsompop K; Adalsteinsson E; Bilgic B
NMR Biomed; 2017 Apr; 30(4):. PubMed ID: 27332141
[TBL] [Abstract][Full Text] [Related]
28. Unsupervised resolution-agnostic quantitative susceptibility mapping using adaptive instance normalization.
Oh G; Bae H; Ahn HS; Park SH; Moon WJ; Ye JC
Med Image Anal; 2022 Jul; 79():102477. PubMed ID: 35605505
[TBL] [Abstract][Full Text] [Related]
29. SHARQnet - Sophisticated harmonic artifact reduction in quantitative susceptibility mapping using a deep convolutional neural network.
Bollmann S; Kristensen MH; Larsen MS; Olsen MV; Pedersen MJ; Østergaard LR; O'Brien K; Langkammer C; Fazlollahi A; Barth M
Z Med Phys; 2019 May; 29(2):139-149. PubMed ID: 30773331
[TBL] [Abstract][Full Text] [Related]
30. Background field removal using a region adaptive kernel for quantitative susceptibility mapping of human brain.
Fang J; Bao L; Li X; van Zijl PCM; Chen Z
J Magn Reson; 2017 Aug; 281():130-140. PubMed ID: 28595120
[TBL] [Abstract][Full Text] [Related]
31. Cerebral metabolic rate of oxygen (CMRO
Cho J; Kee Y; Spincemaille P; Nguyen TD; Zhang J; Gupta A; Zhang S; Wang Y
Magn Reson Med; 2018 Oct; 80(4):1595-1604. PubMed ID: 29516537
[TBL] [Abstract][Full Text] [Related]
32. Recommended implementation of quantitative susceptibility mapping for clinical research in the brain: A consensus of the ISMRM electro-magnetic tissue properties study group.
; Bilgic B; Costagli M; Chan KS; Duyn J; Langkammer C; Lee J; Li X; Liu C; Marques JP; Milovic C; Robinson SD; Schweser F; Shmueli K; Spincemaille P; Straub S; van Zijl P; Wang Y;
Magn Reson Med; 2024 May; 91(5):1834-1862. PubMed ID: 38247051
[TBL] [Abstract][Full Text] [Related]
33. A data-driven deep learning pipeline for quantitative susceptibility mapping (QSM).
Wang Z; Xia P; Huang F; Wei H; Hui ES; Mak HK; Cao P
Magn Reson Imaging; 2022 May; 88():89-100. PubMed ID: 35124180
[TBL] [Abstract][Full Text] [Related]
34. S2Q-Net: Mining the High-Pass Filtered Phase Data in Susceptibility Weighted Imaging for Quantitative Susceptibility Mapping.
Lu Z; Li J; Wang C; Ge R; Chen L; He H; Shi J
IEEE J Biomed Health Inform; 2022 Aug; 26(8):3938-3949. PubMed ID: 35254999
[TBL] [Abstract][Full Text] [Related]
35. An interleaved sequence for simultaneous magnetic resonance angiography (MRA), susceptibility weighted imaging (SWI) and quantitative susceptibility mapping (QSM).
Chen Y; Liu S; Buch S; Hu J; Kang Y; Haacke EM
Magn Reson Imaging; 2018 Apr; 47():1-6. PubMed ID: 29154893
[TBL] [Abstract][Full Text] [Related]
36. NeXtQSM-A complete deep learning pipeline for data-consistent Quantitative Susceptibility Mapping trained with hybrid data.
Cognolato F; O'Brien K; Jin J; Robinson S; Laun FB; Barth M; Bollmann S
Med Image Anal; 2023 Feb; 84():102700. PubMed ID: 36529002
[TBL] [Abstract][Full Text] [Related]
37. Edge prior guided dictionary learning for quantitative susceptibility mapping reconstruction.
Du J; Ji Y; Zhu J; Mai X; Zou J; Chen Y; Gu N
Quant Imaging Med Surg; 2022 Jan; 12(1):510-525. PubMed ID: 34993097
[TBL] [Abstract][Full Text] [Related]
38. Fidelity imposed network edit (FINE) for solving ill-posed image reconstruction.
Zhang J; Liu Z; Zhang S; Zhang H; Spincemaille P; Nguyen TD; Sabuncu MR; Wang Y
Neuroimage; 2020 May; 211():116579. PubMed ID: 31981779
[TBL] [Abstract][Full Text] [Related]
39. Simultaneous voxel-based magnetic susceptibility and morphometry analysis using magnetization-prepared spoiled turbo multiple gradient echo.
Kan H; Uchida Y; Arai N; Ueki Y; Aoki T; Kasai H; Kunitomo H; Hirose Y; Matsukawa N; Shibamoto Y
NMR Biomed; 2020 May; 33(5):e4272. PubMed ID: 32043682
[TBL] [Abstract][Full Text] [Related]
40. Multiecho complex total field inversion method (mcTFI) for improved signal modeling in quantitative susceptibility mapping.
Wen Y; Spincemaille P; Nguyen T; Cho J; Kovanlikaya I; Anderson J; Wu G; Yang B; Fung M; Li K; Kelley D; Benhamo N; Wang Y
Magn Reson Med; 2021 Oct; 86(4):2165-2178. PubMed ID: 34028868
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
