BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

312 related articles for article (PubMed ID: 38009583)

  • 1. MRI motion artifact reduction using a conditional diffusion probabilistic model (MAR-CDPM).
    Safari M; Yang X; Fatemi A; Archambault L
    Med Phys; 2024 Apr; 51(4):2598-2610. PubMed ID: 38009583
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Unsupervised MRI motion artifact disentanglement: introducing MAUDGAN.
    Safari M; Yang X; Chang CW; Qiu RLJ; Fatemi A; Archambault L
    Phys Med Biol; 2024 May; 69(11):. PubMed ID: 38714192
    [No Abstract]   [Full Text] [Related]  

  • 3. Synthesizing high-resolution magnetic resonance imaging using parallel cycle-consistent generative adversarial networks for fast magnetic resonance imaging.
    Xie H; Lei Y; Wang T; Roper J; Dhabaan AH; Bradley JD; Liu T; Mao H; Yang X
    Med Phys; 2022 Jan; 49(1):357-369. PubMed ID: 34821395
    [TBL] [Abstract][Full Text] [Related]  

  • 4. DeepFLAIR: A neural network approach to mitigate signal and contrast loss in temporal lobes at 7 Tesla FLAIR images.
    Uher D; Drenthen GS; Poser BA; Hofman PAM; Wagner LG; van Lanen RHGJ; Hoeberigs CM; Colon AJ; Schijns OEMG; Jansen JFA; Backes WH
    Magn Reson Imaging; 2024 Jul; 110():57-68. PubMed ID: 38621552
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Synthesis of diffusion-weighted MRI scalar maps from FLAIR volumes using generative adversarial networks.
    Chan K; Maralani PJ; Moody AR; Khademi A
    Front Neuroinform; 2023; 17():1197330. PubMed ID: 37603783
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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; 46(12):e823-e834. PubMed ID: 31811792
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Correction of out-of-FOV motion artifacts using convolutional neural network.
    Wang C; Liang Y; Wu Y; Zhao S; Du YP
    Magn Reson Imaging; 2020 Sep; 71():93-102. PubMed ID: 32464243
    [TBL] [Abstract][Full Text] [Related]  

  • 8. High-resolution 3T to 7T ADC map synthesis with a hybrid CNN-transformer model.
    Eidex Z; Wang J; Safari M; Elder E; Wynne J; Wang T; Shu HK; Mao H; Yang X
    Med Phys; 2024 Jun; 51(6):4380-4388. PubMed ID: 38630982
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Unsupervised arterial spin labeling image superresolution via multiscale generative adversarial network.
    Cui J; Gong K; Han P; Liu H; Li Q
    Med Phys; 2022 Apr; 49(4):2373-2385. PubMed ID: 35048390
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Deformable registration of magnetic resonance images using unsupervised deep learning in neuro-/radiation oncology.
    Osman AFI; Al-Mugren KS; Tamam NM; Shahine B
    Radiat Oncol; 2024 May; 19(1):61. PubMed ID: 38773620
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Probabilistic self-learning framework for low-dose CT denoising.
    Bai T; Wang B; Nguyen D; Jiang S
    Med Phys; 2021 May; 48(5):2258-2270. PubMed ID: 33621348
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Deep Learning Based Noise Reduction for Brain MR Imaging: Tests on Phantoms and Healthy Volunteers.
    Kidoh M; Shinoda K; Kitajima M; Isogawa K; Nambu M; Uetani H; Morita K; Nakaura T; Tateishi M; Yamashita Y; Yamashita Y
    Magn Reson Med Sci; 2020 Aug; 19(3):195-206. PubMed ID: 31484849
    [TBL] [Abstract][Full Text] [Related]  

  • 13. DeepSWI: Using Deep Learning to Enhance Susceptibility Contrast on T2*-Weighted MRI.
    Genc O; Morrison MA; Villanueva-Meyer JE; Burns B; Hess CP; Banerjee S; Lupo JM
    J Magn Reson Imaging; 2023 Oct; 58(4):1200-1210. PubMed ID: 36733222
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Swin Transformer and the Unet Architecture to Correct Motion Artifacts in Magnetic Resonance Image Reconstruction.
    Hossain MB; Shinde RK; Imtiaz SM; Hossain FMF; Jeon SH; Kwon KC; Kim N
    Int J Biomed Imaging; 2024; 2024():8972980. PubMed ID: 38725808
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Deep learning-based motion quantification from k-space for fast model-based magnetic resonance imaging motion correction.
    Hossbach J; Splitthoff DN; Cauley S; Clifford B; Polak D; Lo WC; Meyer H; Maier A
    Med Phys; 2023 Apr; 50(4):2148-2161. PubMed ID: 36433748
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Multimodal MRI synthesis using unified generative adversarial networks.
    Dai X; Lei Y; Fu Y; Curran WJ; Liu T; Mao H; Yang X
    Med Phys; 2020 Dec; 47(12):6343-6354. PubMed ID: 33053202
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Deep learning enables reduced gadolinium dose for contrast-enhanced brain MRI.
    Gong E; Pauly JM; Wintermark M; Zaharchuk G
    J Magn Reson Imaging; 2018 Aug; 48(2):330-340. PubMed ID: 29437269
    [TBL] [Abstract][Full Text] [Related]  

  • 18. MC
    Lee J; Kim B; Park H
    Magn Reson Med; 2021 Aug; 86(2):1077-1092. PubMed ID: 33720462
    [TBL] [Abstract][Full Text] [Related]  

  • 19. SEMAC-VAT and MSVAT-SPACE sequence strategies for metal artifact reduction in 1.5T magnetic resonance imaging.
    Ai T; Padua A; Goerner F; Nittka M; Gugala Z; Jadhav S; Trelles M; Johnson RF; Lindsey RW; Li X; Runge VM
    Invest Radiol; 2012 May; 47(5):267-76. PubMed ID: 22266987
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Motion artifacts reduction in brain MRI by means of a deep residual network with densely connected multi-resolution blocks (DRN-DCMB).
    Liu J; Kocak M; Supanich M; Deng J
    Magn Reson Imaging; 2020 Sep; 71():69-79. PubMed ID: 32428549
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.