BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

192 related articles for article (PubMed ID: 35753595)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. Comparison of quantitative susceptibility mapping methods for iron-sensitive susceptibility imaging at 7T: An evaluation in healthy subjects and patients with Huntington's disease.
    Yao J; Morrison MA; Jakary A; Avadiappan S; Chen Y; Luitjens J; Glueck J; Driscoll T; Geschwind MD; Nelson AB; Villanueva-Meyer JE; Hess CP; Lupo JM
    Neuroimage; 2023 Jan; 265():119788. PubMed ID: 36476567
    [TBL] [Abstract][Full Text] [Related]  

  • 5. 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]  

  • 6. 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]  

  • 7. 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]  

  • 8. Affine transformation edited and refined deep neural network for quantitative susceptibility mapping.
    Xiong Z; Gao Y; Liu F; Sun H
    Neuroimage; 2023 Feb; 267():119842. PubMed ID: 36586542
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Investigating the effect of oblique image acquisition on the accuracy of QSM and a robust tilt correction method.
    Kiersnowski OC; Karsa A; Wastling SJ; Thornton JS; Shmueli K
    Magn Reson Med; 2023 May; 89(5):1791-1808. PubMed ID: 36480002
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. 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]  

  • 12. 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]  

  • 13. 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]  

  • 14. Comparison of quantitative susceptibility mapping methods on evaluating radiation-induced cerebral microbleeds and basal ganglia at 3T and 7T.
    Chen Y; Genc O; Poynton CB; Banerjee S; Hess CP; Lupo JM
    NMR Biomed; 2022 May; 35(5):e4666. PubMed ID: 35075701
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Deep grey matter quantitative susceptibility mapping from small spatial coverages using deep learning.
    Zhu X; Gao Y; Liu F; Crozier S; Sun H
    Z Med Phys; 2022 May; 32(2):188-198. PubMed ID: 34312047
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. 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]  

  • 19. Investigating the accuracy and precision of TE-dependent versus multi-echo QSM using Laplacian-based methods at 3 T.
    Biondetti E; Karsa A; Thomas DL; Shmueli K
    Magn Reson Med; 2020 Dec; 84(6):3040-3053. PubMed ID: 32491224
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Quantitative susceptibility mapping using a superposed dipole inversion method: Application to intracranial hemorrhage.
    Sun H; Kate M; Gioia LC; Emery DJ; Butcher K; Wilman AH
    Magn Reson Med; 2016 Sep; 76(3):781-91. PubMed ID: 26414757
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.