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Journal Abstract Search

4879 related items for PubMed ID: 30480818

  • 21. Gross tumor volume segmentation for head and neck cancer radiotherapy using deep dense multi-modality network.
    Guo Z, Guo N, Gong K, Zhong S, Li Q.
    Phys Med Biol; 2019 Oct 16; 64(20):205015. PubMed ID: 31514173
    [Abstract] [Full Text] [Related]

  • 22. A slice classification model-facilitated 3D encoder-decoder network for segmenting organs at risk in head and neck cancer.
    Zhang S, Wang H, Tian S, Zhang X, Li J, Lei R, Gao M, Liu C, Yang L, Bi X, Zhu L, Zhu S, Xu T, Yang R.
    J Radiat Res; 2021 Jan 01; 62(1):94-103. PubMed ID: 33029634
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  • 23. Automatic clinical target volume delineation for cervical cancer in CT images using deep learning.
    Shi J, Ding X, Liu X, Li Y, Liang W, Wu J.
    Med Phys; 2021 Jul 01; 48(7):3968-3981. PubMed ID: 33905545
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  • 24. Clinical Validation of a Deep-Learning Segmentation Software in Head and Neck: An Early Analysis in a Developing Radiation Oncology Center.
    D'Aviero A, Re A, Catucci F, Piccari D, Votta C, Piro D, Piras A, Di Dio C, Iezzi M, Preziosi F, Menna S, Quaranta F, Boschetti A, Marras M, Miccichè F, Gallus R, Indovina L, Bussu F, Valentini V, Cusumano D, Mattiucci GC.
    Int J Environ Res Public Health; 2022 Jul 25; 19(15):. PubMed ID: 35897425
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  • 25. Cascaded deep learning-based auto-segmentation for head and neck cancer patients: Organs at risk on T2-weighted magnetic resonance imaging.
    Korte JC, Hardcastle N, Ng SP, Clark B, Kron T, Jackson P.
    Med Phys; 2021 Dec 25; 48(12):7757-7772. PubMed ID: 34676555
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  • 26. Auto-segmentation of organs at risk for head and neck radiotherapy planning: From atlas-based to deep learning methods.
    Vrtovec T, Močnik D, Strojan P, Pernuš F, Ibragimov B.
    Med Phys; 2020 Sep 25; 47(9):e929-e950. PubMed ID: 32510603
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  • 27. Multi-modal segmentation with missing image data for automatic delineation of gross tumor volumes in head and neck cancers.
    Zhao Y, Wang X, Phan J, Chen X, Lee A, Yu C, Huang K, Court LE, Pan T, Wang H, Wahid KA, Mohamed ASR, Naser M, Fuller CD, Yang J.
    Med Phys; 2024 Oct 25; 51(10):7295-7307. PubMed ID: 38896829
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  • 28. Validation of clinical acceptability of an atlas-based segmentation algorithm for the delineation of organs at risk in head and neck cancer.
    Hoang Duc AK, Eminowicz G, Mendes R, Wong SL, McClelland J, Modat M, Cardoso MJ, Mendelson AF, Veiga C, Kadir T, D'Souza D, Ourselin S.
    Med Phys; 2015 Sep 25; 42(9):5027-34. PubMed ID: 26328953
    [Abstract] [Full Text] [Related]

  • 29. HaN-Seg: The head and neck organ-at-risk CT and MR segmentation dataset.
    Podobnik G, Strojan P, Peterlin P, Ibragimov B, Vrtovec T.
    Med Phys; 2023 Mar 25; 50(3):1917-1927. PubMed ID: 36594372
    [Abstract] [Full Text] [Related]

  • 30. A convolutional neural network algorithm for automatic segmentation of head and neck organs at risk using deep lifelong learning.
    Chan JW, Kearney V, Haaf S, Wu S, Bogdanov M, Reddick M, Dixit N, Sudhyadhom A, Chen J, Yom SS, Solberg TD.
    Med Phys; 2019 May 25; 46(5):2204-2213. PubMed ID: 30887523
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  • 31. Multi-organ segmentation of the head and neck area: an efficient hierarchical neural networks approach.
    Tappeiner E, Pröll S, Hönig M, Raudaschl PF, Zaffino P, Spadea MF, Sharp GC, Schubert R, Fritscher K.
    Int J Comput Assist Radiol Surg; 2019 May 25; 14(5):745-754. PubMed ID: 30847761
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  • 32. Comparative clinical evaluation of atlas and deep-learning-based auto-segmentation of organ structures in liver cancer.
    Ahn SH, Yeo AU, Kim KH, Kim C, Goh Y, Cho S, Lee SB, Lim YK, Kim H, Shin D, Kim T, Kim TH, Youn SH, Oh ES, Jeong JH.
    Radiat Oncol; 2019 Nov 27; 14(1):213. PubMed ID: 31775825
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  • 33. 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 27; 40(7):071905. PubMed ID: 23822442
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  • 34. Deep learning-based auto segmentation using generative adversarial network on magnetic resonance images obtained for head and neck cancer patients.
    Kawahara D, Tsuneda M, Ozawa S, Okamoto H, Nakamura M, Nishio T, Nagata Y.
    J Appl Clin Med Phys; 2022 May 27; 23(5):e13579. PubMed ID: 35263027
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  • 35. Automated delineation of head and neck organs at risk using synthetic MRI-aided mask scoring regional convolutional neural network.
    Dai X, Lei Y, Wang T, Zhou J, Roper J, McDonald M, Beitler JJ, Curran WJ, Liu T, Yang X.
    Med Phys; 2021 Oct 27; 48(10):5862-5873. PubMed ID: 34342878
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  • 36. Evaluation of segmentation methods on head and neck CT: Auto-segmentation challenge 2015.
    Raudaschl PF, Zaffino P, Sharp GC, Spadea MF, Chen A, Dawant BM, Albrecht T, Gass T, Langguth C, Lüthi M, Jung F, Knapp O, Wesarg S, Mannion-Haworth R, Bowes M, Ashman A, Guillard G, Brett A, Vincent G, Orbes-Arteaga M, Cárdenas-Peña D, Castellanos-Dominguez G, Aghdasi N, Li Y, Berens A, Moe K, Hannaford B, Schubert R, Fritscher KD.
    Med Phys; 2017 May 27; 44(5):2020-2036. PubMed ID: 28273355
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  • 37. U-net architecture with embedded Inception-ResNet-v2 image encoding modules for automatic segmentation of organs-at-risk in head and neck cancer radiation therapy based on computed tomography scans.
    Siciarz P, McCurdy B.
    Phys Med Biol; 2022 Jun 22; 67(11):. PubMed ID: 35134792
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  • 38. Multi-View Spatial Aggregation Framework for Joint Localization and Segmentation of Organs at Risk in Head and Neck CT Images.
    Liang S, Thung KH, Nie D, Zhang Y, Shen D.
    IEEE Trans Med Imaging; 2020 Sep 22; 39(9):2794-2805. PubMed ID: 32091997
    [Abstract] [Full Text] [Related]

  • 39. [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 22; 51(3):2187-2199. PubMed ID: 38319676
    [Abstract] [Full Text] [Related]

  • 40. Clinical evaluation of deep learning and atlas-based auto-segmentation for critical organs at risk in radiation therapy.
    Gibbons E, Hoffmann M, Westhuyzen J, Hodgson A, Chick B, Last A.
    J Med Radiat Sci; 2023 Apr 22; 70 Suppl 2(Suppl 2):15-25. PubMed ID: 36148621
    [Abstract] [Full Text] [Related]

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