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Journal Abstract Search

717 related items for PubMed ID: 35493368

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  • 6. Segmentation of organs-at-risks in head and neck CT images using convolutional neural networks.
    Ibragimov B, Xing L.
    Med Phys; 2017 Feb; 44(2):547-557. PubMed ID: 28205307
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  • 8. Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.
    Kawula M, Hadi I, Nierer L, Vagni M, Cusumano D, Boldrini L, Placidi L, Corradini S, Belka C, Landry G, Kurz C.
    Med Phys; 2023 Mar; 50(3):1573-1585. PubMed ID: 36259384
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  • 12. Segmentation of organs-at-risk in cervical cancer CT images with a convolutional neural network.
    Liu Z, Liu X, Xiao B, Wang S, Miao Z, Sun Y, Zhang F.
    Phys Med; 2020 Jan; 69():184-191. PubMed ID: 31918371
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  • 13. A deep image-to-image network organ segmentation algorithm for radiation treatment planning: principles and evaluation.
    Marschner S, Datar M, Gaasch A, Xu Z, Grbic S, Chabin G, Geiger B, Rosenman J, Corradini S, Niyazi M, Heimann T, Möhler C, Vega F, Belka C, Thieke C.
    Radiat Oncol; 2022 Jul 22; 17(1):129. PubMed ID: 35869525
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  • 14. Automatic segmentation and applicator reconstruction for CT-based brachytherapy of cervical cancer using 3D convolutional neural networks.
    Zhang D, Yang Z, Jiang S, Zhou Z, Meng M, Wang W.
    J Appl Clin Med Phys; 2020 Oct 22; 21(10):158-169. PubMed ID: 32991783
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  • 16. [Automatic segmentation of head and neck organs at risk based on three-dimensional U-NET deep convolutional neural network].
    Dai X, Wang X, Du L, Ma N, Xu S, Cai B, Wang S, Wang Z, Qu B.
    Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2020 Feb 25; 37(1):136-141. PubMed ID: 32096387
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