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Journal Abstract Search

302 related items for PubMed ID: 30847761

  • 21.
    ; . PubMed ID:
    [No Abstract] [Full Text] [Related]

  • 22. [Not Available].
    Zhang L, Liu Z, Zhang L, Wu Z, Yu X, Holmes J, Feng H, Dai H, Li X, Li Q, Wong WW, Vora SA, Zhu D, Liu T, Liu W.
    Med Phys; 2024 Mar; 51(3):2187-2199. PubMed ID: 38319676
    [Abstract] [Full Text] [Related]

  • 23. A neural network approach for fast, automated quantification of DIR performance.
    Neylon J, Min Y, Low DA, Santhanam A.
    Med Phys; 2017 Aug; 44(8):4126-4138. PubMed ID: 28477340
    [Abstract] [Full Text] [Related]

  • 24. Automatic Segmentation of Multiple Organs on 3D CT Images by Using Deep Learning Approaches.
    Zhou X.
    Adv Exp Med Biol; 2020 Aug; 1213():135-147. PubMed ID: 32030668
    [Abstract] [Full Text] [Related]

  • 25. VoxResNet: Deep voxelwise residual networks for brain segmentation from 3D MR images.
    Chen H, Dou Q, Yu L, Qin J, Heng PA.
    Neuroimage; 2018 Apr 15; 170():446-455. PubMed ID: 28445774
    [Abstract] [Full Text] [Related]

  • 26. FocusNetv2: Imbalanced large and small organ segmentation with adversarial shape constraint for head and neck CT images.
    Gao Y, Huang R, Yang Y, Zhang J, Shao K, Tao C, Chen Y, Metaxas DN, Li H, Chen M.
    Med Image Anal; 2021 Jan 15; 67():101831. PubMed ID: 33129144
    [Abstract] [Full Text] [Related]

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  • 29. Improving automatic delineation for head and neck organs at risk by Deep Learning Contouring.
    van Dijk LV, Van den Bosch L, Aljabar P, Peressutti D, Both S, J H M Steenbakkers R, Langendijk JA, Gooding MJ, Brouwer CL.
    Radiother Oncol; 2020 Jan 15; 142():115-123. PubMed ID: 31653573
    [Abstract] [Full Text] [Related]

  • 30. Evaluation of auto-segmentation accuracy of cloud-based artificial intelligence and atlas-based models.
    Urago Y, Okamoto H, Kaneda T, Murakami N, Kashihara T, Takemori M, Nakayama H, Iijima K, Chiba T, Kuwahara J, Katsuta S, Nakamura S, Chang W, Saitoh H, Igaki H.
    Radiat Oncol; 2021 Sep 09; 16(1):175. PubMed ID: 34503533
    [Abstract] [Full Text] [Related]

  • 31. Deep learning vs. atlas-based models for fast auto-segmentation of the masticatory muscles on head and neck CT images.
    Chen W, Li Y, Dyer BA, Feng X, Rao S, Benedict SH, Chen Q, Rong Y.
    Radiat Oncol; 2020 Jul 20; 15(1):176. PubMed ID: 32690103
    [Abstract] [Full Text] [Related]

  • 32. A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy.
    Chen X, Sun S, Bai N, Han K, Liu Q, Yao S, Tang H, Zhang C, Lu Z, Huang Q, Zhao G, Xu Y, Chen T, Xie X, Liu Y.
    Radiother Oncol; 2021 Jul 20; 160():175-184. PubMed ID: 33961914
    [Abstract] [Full Text] [Related]

  • 33. Automatic 3D liver location and segmentation via convolutional neural network and graph cut.
    Lu F, Wu F, Hu P, Peng Z, Kong D.
    Int J Comput Assist Radiol Surg; 2017 Feb 20; 12(2):171-182. PubMed ID: 27604760
    [Abstract] [Full Text] [Related]

  • 34. Automatic multi-organ segmentation in computed tomography images using hierarchical convolutional neural network.
    Sultana S, Robinson A, Song DY, Lee J.
    J Med Imaging (Bellingham); 2020 Sep 20; 7(5):055001. PubMed ID: 33102622
    [Abstract] [Full Text] [Related]

  • 35. 3D deeply supervised network for automated segmentation of volumetric medical images.
    Dou Q, Yu L, Chen H, Jin Y, Yang X, Qin J, Heng PA.
    Med Image Anal; 2017 Oct 20; 41():40-54. PubMed ID: 28526212
    [Abstract] [Full Text] [Related]

  • 36. Tissue segmentation of head and neck CT images for treatment planning: a multiatlas approach combined with intensity modeling.
    Fortunati V, Verhaart RF, van der Lijn F, Niessen WJ, Veenland JF, Paulides MM, van Walsum T.
    Med Phys; 2013 Jul 20; 40(7):071905. PubMed ID: 23822442
    [Abstract] [Full Text] [Related]

  • 37. MHL-Net: A Multistage Hierarchical Learning Network for Head and Neck Multiorgan Segmentation.
    Wang J, Peng Y.
    IEEE J Biomed Health Inform; 2023 Aug 20; 27(8):4074-4085. PubMed ID: 37171918
    [Abstract] [Full Text] [Related]

  • 38. Abdominal multi-organ segmentation with organ-attention networks and statistical fusion.
    Wang Y, Zhou Y, Shen W, Park S, Fishman EK, Yuille AL.
    Med Image Anal; 2019 Jul 20; 55():88-102. PubMed ID: 31035060
    [Abstract] [Full Text] [Related]

  • 39. Comparison of the automatic segmentation of multiple organs at risk in CT images of lung cancer between deep convolutional neural network-based and atlas-based techniques.
    Zhu J, Zhang J, Qiu B, Liu Y, Liu X, Chen L.
    Acta Oncol; 2019 Feb 20; 58(2):257-264. PubMed ID: 30398090
    [Abstract] [Full Text] [Related]

  • 40.
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