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Journal Abstract Search

1156 related items for PubMed ID: 32012292

  • 1. Pseudo-CT generation from multi-parametric MRI using a novel multi-channel multi-path conditional generative adversarial network for nasopharyngeal carcinoma patients.
    Tie X, Lam SK, Zhang Y, Lee KH, Au KH, Cai J.
    Med Phys; 2020 Apr; 47(4):1750-1762. PubMed ID: 32012292
    [Abstract] [Full Text] [Related]

  • 2. Generating synthetic CTs from magnetic resonance images using generative adversarial networks.
    Emami H, Dong M, Nejad-Davarani SP, Glide-Hurst CK.
    Med Phys; 2018 Jun 14. PubMed ID: 29901223
    [Abstract] [Full Text] [Related]

  • 3. Magnetic resonance-based synthetic computed tomography images generated using generative adversarial networks for nasopharyngeal carcinoma radiotherapy treatment planning.
    Peng Y, Chen S, Qin A, Chen M, Gao X, Liu Y, Miao J, Gu H, Zhao C, Deng X, Qi Z.
    Radiother Oncol; 2020 Sep 14; 150():217-224. PubMed ID: 32622781
    [Abstract] [Full Text] [Related]

  • 4. A prior-information-based automatic segmentation method for the clinical target volume in adaptive radiotherapy of cervical cancer.
    Wang X, Chang Y, Pei X, Xu XG.
    J Appl Clin Med Phys; 2024 May 14; 25(5):e14350. PubMed ID: 38546277
    [Abstract] [Full Text] [Related]

  • 5. Compensation cycle consistent generative adversarial networks (Comp-GAN) for synthetic CT generation from MR scans with truncated anatomy.
    Zhao Y, Wang H, Yu C, Court LE, Wang X, Wang Q, Pan T, Ding Y, Phan J, Yang J.
    Med Phys; 2023 Jul 14; 50(7):4399-4414. PubMed ID: 36698291
    [Abstract] [Full Text] [Related]

  • 6. Synthetic CT reconstruction using a deep spatial pyramid convolutional framework for MR-only breast radiotherapy.
    Olberg S, Zhang H, Kennedy WR, Chun J, Rodriguez V, Zoberi I, Thomas MA, Kim JS, Mutic S, Green OL, Park JC.
    Med Phys; 2019 Sep 14; 46(9):4135-4147. PubMed ID: 31309586
    [Abstract] [Full Text] [Related]

  • 7. Deep learning approaches using 2D and 3D convolutional neural networks for generating male pelvic synthetic computed tomography from magnetic resonance imaging.
    Fu J, Yang Y, Singhrao K, Ruan D, Chu FI, Low DA, Lewis JH.
    Med Phys; 2019 Sep 14; 46(9):3788-3798. PubMed ID: 31220353
    [Abstract] [Full Text] [Related]

  • 8. Shape constrained fully convolutional DenseNet with adversarial training for multiorgan segmentation on head and neck CT and low-field MR images.
    Tong N, Gou S, Yang S, Cao M, Sheng K.
    Med Phys; 2019 Jun 14; 46(6):2669-2682. PubMed ID: 31002188
    [Abstract] [Full Text] [Related]

  • 9. Multi-sequence MR image-based synthetic CT generation using a generative adversarial network for head and neck MRI-only radiotherapy.
    Qi M, Li Y, Wu A, Jia Q, Li B, Sun W, Dai Z, Lu X, Zhou L, Deng X, Song T.
    Med Phys; 2020 Apr 14; 47(4):1880-1894. PubMed ID: 32027027
    [Abstract] [Full Text] [Related]

  • 10. Synthesis of pseudo-CT images from pelvic MRI images based on an MD-CycleGAN model for radiotherapy.
    Sun H, Xi Q, Fan R, Sun J, Xie K, Ni X, Yang J.
    Phys Med Biol; 2022 Jan 28; 67(3):. PubMed ID: 34879356
    [Abstract] [Full Text] [Related]

  • 11. MR-based synthetic CT generation using a deep convolutional neural network method.
    Han X.
    Med Phys; 2017 Apr 28; 44(4):1408-1419. PubMed ID: 28192624
    [Abstract] [Full Text] [Related]

  • 12. MRI-only based synthetic CT generation using dense cycle consistent generative adversarial networks.
    Lei Y, Harms J, Wang T, Liu Y, Shu HK, Jani AB, Curran WJ, Mao H, Liu T, Yang X.
    Med Phys; 2019 Aug 28; 46(8):3565-3581. PubMed ID: 31112304
    [Abstract] [Full Text] [Related]

  • 13. MR-based synthetic CT image for intensity-modulated proton treatment planning of nasopharyngeal carcinoma patients.
    Chen S, Peng Y, Qin A, Liu Y, Zhao C, Deng X, Deraniyagala R, Stevens C, Ding X.
    Acta Oncol; 2022 Nov 28; 61(11):1417-1424. PubMed ID: 36305424
    [Abstract] [Full Text] [Related]

  • 14. Improving CBCT quality to CT level using deep learning with generative adversarial network.
    Zhang Y, Yue N, Su MY, Liu B, Ding Y, Zhou Y, Wang H, Kuang Y, Nie K.
    Med Phys; 2021 Jun 28; 48(6):2816-2826. PubMed ID: 33259647
    [Abstract] [Full Text] [Related]

  • 15. A new deep convolutional neural network design with efficient learning capability: Application to CT image synthesis from MRI.
    Bahrami A, Karimian A, Fatemizadeh E, Arabi H, Zaidi H.
    Med Phys; 2020 Oct 28; 47(10):5158-5171. PubMed ID: 32730661
    [Abstract] [Full Text] [Related]

  • 16. Research on obtaining pseudo CT images based on stacked generative adversarial network.
    Sun H, Lu Z, Fan R, Xiong W, Xie K, Ni X, Yang J.
    Quant Imaging Med Surg; 2021 May 28; 11(5):1983-2000. PubMed ID: 33936980
    [Abstract] [Full Text] [Related]

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  • 18. Multi-planar dual adversarial network based on dynamic 3D features for MRI-CT head and neck image synthesis.
    Touati R, Trung Le W, Kadoury S.
    Phys Med Biol; 2024 Jul 19; 69(15):. PubMed ID: 38981593
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