These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

201 related items for PubMed ID: 35403237

  • 1. Mitigating transmit-B1 artifacts by predicting parallel transmission images with deep learning: A feasibility study using high-resolution whole-brain diffusion at 7 Tesla.
    Ma X, Uğurbil K, Wu X.
    Magn Reson Med; 2022 Aug; 88(2):727-741. PubMed ID: 35403237
    [Abstract] [Full Text] [Related]

  • 2. High-resolution whole-brain diffusion MRI at 7T using radiofrequency parallel transmission.
    Wu X, Auerbach EJ, Vu AT, Moeller S, Lenglet C, Schmitter S, Van de Moortele PF, Yacoub E, Uğurbil K.
    Magn Reson Med; 2018 Nov; 80(5):1857-1870. PubMed ID: 29603381
    [Abstract] [Full Text] [Related]

  • 3. MRI Gibbs-ringing artifact reduction by means of machine learning using convolutional neural networks.
    Zhang Q, Ruan G, Yang W, Liu Y, Zhao K, Feng Q, Chen W, Wu EX, Feng Y.
    Magn Reson Med; 2019 Dec; 82(6):2133-2145. PubMed ID: 31373061
    [Abstract] [Full Text] [Related]

  • 4. A field-monitoring-based approach for correcting eddy-current-induced artifacts of up to the 2nd spatial order in human-connectome-project-style multiband diffusion MRI experiment at 7T: A pilot study.
    Ma R, Akçakaya M, Moeller S, Auerbach E, Uğurbil K, Van de Moortele PF.
    Neuroimage; 2020 Aug 01; 216():116861. PubMed ID: 32305565
    [Abstract] [Full Text] [Related]

  • 5. Human Connectome Project-style resting-state functional MRI at 7 Tesla using radiofrequency parallel transmission.
    Wu X, Auerbach EJ, Vu AT, Moeller S, Van de Moortele PF, Yacoub E, Uğurbil K.
    Neuroimage; 2019 Jan 01; 184():396-408. PubMed ID: 30237033
    [Abstract] [Full Text] [Related]

  • 6. Fast learning of fiber orientation distribution function for MR tractography using convolutional neural network.
    Lin Z, Gong T, Wang K, Li Z, He H, Tong Q, Yu F, Zhong J.
    Med Phys; 2019 Jul 01; 46(7):3101-3116. PubMed ID: 31009085
    [Abstract] [Full Text] [Related]

  • 7. SDnDTI: Self-supervised deep learning-based denoising for diffusion tensor MRI.
    Tian Q, Li Z, Fan Q, Polimeni JR, Bilgic B, Salat DH, Huang SY.
    Neuroimage; 2022 Jun 01; 253():119033. PubMed ID: 35240299
    [Abstract] [Full Text] [Related]

  • 8. Deep learning based multiplexed sensitivity-encoding (DL-MUSE) for high-resolution multi-shot DWI.
    Zhang H, Wang C, Chen W, Wang F, Yang Z, Xu S, Wang H.
    Neuroimage; 2021 Dec 01; 244():118632. PubMed ID: 34627977
    [Abstract] [Full Text] [Related]

  • 9. Unsupervised Deep Learning for FOD-Based Susceptibility Distortion Correction in Diffusion MRI.
    Qiao Y, Shi Y.
    IEEE Trans Med Imaging; 2022 May 01; 41(5):1165-1175. PubMed ID: 34882551
    [Abstract] [Full Text] [Related]

  • 10. Unsupervised motion artifact correction of turbo spin-echo MRI using deep image prior.
    Lee J, Seo H, Lee W, Park H.
    Magn Reson Med; 2024 Jul 01; 92(1):28-42. PubMed ID: 38282279
    [Abstract] [Full Text] [Related]

  • 11. Simultaneous multi-slice image reconstruction using regularized image domain split slice-GRAPPA for diffusion MRI.
    HashemizadehKolowri SK, Chen RR, Adluru G, Dean DC, Wilde EA, Alexander AL, DiBella EVR.
    Med Image Anal; 2021 May 01; 70():102000. PubMed ID: 33676098
    [Abstract] [Full Text] [Related]

  • 12. Metal artifact reduction for practical dental computed tomography by improving interpolation-based reconstruction with deep learning.
    Liang K, Zhang L, Yang H, Yang Y, Chen Z, Xing Y.
    Med Phys; 2019 Dec 01; 46(12):e823-e834. PubMed ID: 31811792
    [Abstract] [Full Text] [Related]

  • 13. [Improvement of Motion Artifacts in Brain MRI Using Deep Learning by Simulation Training Data].
    Muro I, Shimizu S, Tsukamoto H.
    Nihon Hoshasen Gijutsu Gakkai Zasshi; 2022 Dec 01; 78(1):13-22. PubMed ID: 35046218
    [Abstract] [Full Text] [Related]

  • 14. Data-driven synthetic MRI FLAIR artifact correction via deep neural network.
    Ryu K, Nam Y, Gho SM, Jang J, Lee HJ, Cha J, Baek HJ, Park J, Kim DH.
    J Magn Reson Imaging; 2019 Nov 01; 50(5):1413-1423. PubMed ID: 30884007
    [Abstract] [Full Text] [Related]

  • 15. Deep convolution neural networks based artifact suppression in under-sampled radial acquisitions of myocardial T 1 mapping images.
    Nezafat M, El-Rewaidy H, Kucukseymen S, Hauser TH, Fahmy AS.
    Phys Med Biol; 2020 Nov 24; 65(22):225024. PubMed ID: 33045693
    [Abstract] [Full Text] [Related]

  • 16. A deep learning method for eliminating head motion artifacts in computed tomography.
    Su B, Wen Y, Liu Y, Liao S, Fu J, Quan G, Li Z.
    Med Phys; 2022 Jan 24; 49(1):411-419. PubMed ID: 34786714
    [Abstract] [Full Text] [Related]

  • 17. Diffusion MRI data analysis assisted by deep learning synthesized anatomical images (DeepAnat).
    Li Z, Fan Q, Bilgic B, Wang G, Wu W, Polimeni JR, Miller KL, Huang SY, Tian Q.
    Med Image Anal; 2023 May 24; 86():102744. PubMed ID: 36867912
    [Abstract] [Full Text] [Related]

  • 18. Deep learning based correction of RF field induced inhomogeneities for T2w prostate imaging at 7 T.
    Harrevelt SD, Meliado EFM, van Lier ALHMW, Reesink D, Meijer RP, Pluim JPW, Raaijmakers AJE.
    NMR Biomed; 2023 Dec 24; 36(12):e5019. PubMed ID: 37622473
    [Abstract] [Full Text] [Related]

  • 19. Uncertainty modelling in deep learning for safer neuroimage enhancement: Demonstration in diffusion MRI.
    Tanno R, Worrall DE, Kaden E, Ghosh A, Grussu F, Bizzi A, Sotiropoulos SN, Criminisi A, Alexander DC.
    Neuroimage; 2021 Jan 15; 225():117366. PubMed ID: 33039617
    [Abstract] [Full Text] [Related]

  • 20. FOD-Net: A deep learning method for fiber orientation distribution angular super resolution.
    Zeng R, Lv J, Wang H, Zhou L, Barnett M, Calamante F, Wang C.
    Med Image Anal; 2022 Jul 15; 79():102431. PubMed ID: 35397471
    [Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 11.