312 related articles for article (PubMed ID: 31377323)
1. Learning-based single-step quantitative susceptibility mapping reconstruction without brain extraction.
Wei H; Cao S; Zhang Y; Guan X; Yan F; Yeom KW; Liu C
Neuroimage; 2019 Nov; 202():116064. PubMed ID: 31377323
[TBL] [Abstract][Full Text] [Related]
2. Towards in vivo ground truth susceptibility for single-orientation deep learning QSM: A multi-orientation gradient-echo MRI dataset.
Shi Y; Feng R; Li Z; Zhuang J; Zhang Y; Wei H
Neuroimage; 2022 Nov; 261():119522. PubMed ID: 35905811
[TBL] [Abstract][Full Text] [Related]
3. Quantitative susceptibility mapping using deep neural network: QSMnet.
Yoon J; Gong E; Chatnuntawech I; Bilgic B; Lee J; Jung W; Ko J; Jung H; Setsompop K; Zaharchuk G; Kim EY; Pauly J; Lee J
Neuroimage; 2018 Oct; 179():199-206. PubMed ID: 29894829
[TBL] [Abstract][Full Text] [Related]
4. MoDL-QSM: Model-based deep learning for quantitative susceptibility mapping.
Feng R; Zhao J; Wang H; Yang B; Feng J; Shi Y; Zhang M; Liu C; Zhang Y; Zhuang J; Wei H
Neuroimage; 2021 Oct; 240():118376. PubMed ID: 34246768
[TBL] [Abstract][Full Text] [Related]
5. A subject-specific unsupervised deep learning method for quantitative susceptibility mapping using implicit neural representation.
Zhang M; Feng R; Li Z; Feng J; Wu Q; Zhang Z; Ma C; Wu J; Yan F; Liu C; Zhang Y; Wei H
Med Image Anal; 2024 Jul; 95():103173. PubMed ID: 38657424
[TBL] [Abstract][Full Text] [Related]
6. Instant tissue field and magnetic susceptibility mapping from MRI raw phase using Laplacian enhanced deep neural networks.
Gao Y; Xiong Z; Fazlollahi A; Nestor PJ; Vegh V; Nasrallah F; Winter C; Pike GB; Crozier S; Liu F; Sun H
Neuroimage; 2022 Oct; 259():119410. PubMed ID: 35753595
[TBL] [Abstract][Full Text] [Related]
7. Accelerating quantitative susceptibility and R2* mapping using incoherent undersampling and deep neural network reconstruction.
Gao Y; Cloos M; Liu F; Crozier S; Pike GB; Sun H
Neuroimage; 2021 Oct; 240():118404. PubMed ID: 34280526
[TBL] [Abstract][Full Text] [Related]
8. Joint 2D and 3D phase processing for quantitative susceptibility mapping: application to 2D echo-planar imaging.
Wei H; Zhang Y; Gibbs E; Chen NK; Wang N; Liu C
NMR Biomed; 2017 Apr; 30(4):. PubMed ID: 26887812
[TBL] [Abstract][Full Text] [Related]
9. Deep learning-based quantitative susceptibility mapping (QSM) in the presence of fat using synthetically generated multi-echo phase training data.
Hanspach J; Bollmann S; Grigo J; Karius A; Uder M; Laun FB
Magn Reson Med; 2022 Oct; 88(4):1548-1560. PubMed ID: 35713187
[TBL] [Abstract][Full Text] [Related]
10. A preliminary attempt to visualize nigrosome 1 in the substantia nigra for Parkinson's disease at 3T: An efficient susceptibility map-weighted imaging (SMWI) with quantitative susceptibility mapping using deep neural network (QSMnet).
Jo M; Oh SH
Med Phys; 2020 Mar; 47(3):1151-1160. PubMed ID: 31883389
[TBL] [Abstract][Full Text] [Related]
11. Plug-and-Play latent feature editing for orientation-adaptive quantitative susceptibility mapping neural networks.
Gao Y; Xiong Z; Shan S; Liu Y; Rong P; Li M; Wilman AH; Pike GB; Liu F; Sun H
Med Image Anal; 2024 May; 94():103160. PubMed ID: 38552528
[TBL] [Abstract][Full Text] [Related]
12. Overview of quantitative susceptibility mapping using deep learning: Current status, challenges and opportunities.
Jung W; Bollmann S; Lee J
NMR Biomed; 2022 Apr; 35(4):e4292. PubMed ID: 32207195
[TBL] [Abstract][Full Text] [Related]
13. SEPIA-Susceptibility mapping pipeline tool for phase images.
Chan KS; Marques JP
Neuroimage; 2021 Feb; 227():117611. PubMed ID: 33309901
[TBL] [Abstract][Full Text] [Related]
14. Multi-echo dipole inversion for magnetic susceptibility mapping.
Kames C; Doucette J; Rauscher A
Magn Reson Med; 2023 Jun; 89(6):2391-2401. PubMed ID: 36695283
[TBL] [Abstract][Full Text] [Related]
15. Exploring linearity of deep neural network trained QSM: QSMnet
Jung W; Yoon J; Ji S; Choi JY; Kim JM; Nam Y; Kim EY; Lee J
Neuroimage; 2020 May; 211():116619. PubMed ID: 32044437
[TBL] [Abstract][Full Text] [Related]
16. Whole head quantitative susceptibility mapping using a least-norm direct dipole inversion method.
Sun H; Ma Y; MacDonald ME; Pike GB
Neuroimage; 2018 Oct; 179():166-175. PubMed ID: 29906634
[TBL] [Abstract][Full Text] [Related]
17. QSMART: Quantitative susceptibility mapping artifact reduction technique.
Yaghmaie N; Syeda WT; Wu C; Zhang Y; Zhang TD; Burrows EL; Brodtmann A; Moffat BA; Wright DK; Glarin R; Kolbe S; Johnston LA
Neuroimage; 2021 May; 231():117701. PubMed ID: 33484853
[TBL] [Abstract][Full Text] [Related]
18. BFRnet: A deep learning-based MR background field removal method for QSM of the brain containing significant pathological susceptibility sources.
Zhu X; Gao Y; Liu F; Crozier S; Sun H
Z Med Phys; 2023 Nov; 33(4):578-590. PubMed ID: 36064695
[TBL] [Abstract][Full Text] [Related]
19. Morphology-adaptive total variation for the reconstruction of quantitative susceptibility map from the magnetic resonance imaging phase.
Guo L; Mei Y; Guan J; Tan X; Xu Y; Chen W; Feng Q; Feng Y
PLoS One; 2018; 13(5):e0196922. PubMed ID: 29738526
[TBL] [Abstract][Full Text] [Related]
20. Quantitative Susceptibility Mapping (QSM) Algorithms: Mathematical Rationale and Computational Implementations.
Kee Y; Liu Z; Zhou L; Dimov A; Cho J; de Rochefort L; Seo JK; Wang Y
IEEE Trans Biomed Eng; 2017 Nov; 64(11):2531-2545. PubMed ID: 28885147
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
