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Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

374 related items for PubMed ID: 36148621

  • 21.
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  • 22. Evaluation of auto-segmentation for brachytherapy of postoperative cervical cancer using deep learning-based workflow.
    Wang J, Chen Y, Tu Y, Xie H, Chen Y, Luo L, Zhou P, Tang Q.
    Phys Med Biol; 2023 Feb 23; 68(5):. PubMed ID: 36753762
    [Abstract] [Full Text] [Related]

  • 23. A Preliminary Experience of Implementing Deep-Learning Based Auto-Segmentation in Head and Neck Cancer: A Study on Real-World Clinical Cases.
    Zhong Y, Yang Y, Fang Y, Wang J, Hu W.
    Front Oncol; 2021 Feb 23; 11():638197. PubMed ID: 34026615
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  • 24. A comparative study of auto-contouring softwares in delineation of organs at risk in lung cancer and rectal cancer.
    Chen W, Wang C, Zhan W, Jia Y, Ruan F, Qiu L, Yang S, Li Y.
    Sci Rep; 2021 Nov 26; 11(1):23002. PubMed ID: 34836989
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  • 26. AnatomyNet: Deep learning for fast and fully automated whole-volume segmentation of head and neck anatomy.
    Zhu W, Huang Y, Zeng L, Chen X, Liu Y, Qian Z, Du N, Fan W, Xie X.
    Med Phys; 2019 Feb 26; 46(2):576-589. PubMed ID: 30480818
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  • 30. Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy.
    Savenije MHF, Maspero M, Sikkes GG, van der Voort van Zyp JRN, T J Kotte AN, Bol GH, T van den Berg CA.
    Radiat Oncol; 2020 May 11; 15(1):104. PubMed ID: 32393280
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  • 32. Evaluation Exploration of Atlas-Based and Deep Learning-Based Automatic Contouring for Nasopharyngeal Carcinoma.
    Wang J, Chen Z, Yang C, Qu B, Ma L, Fan W, Zhou Q, Zheng Q, Xu S.
    Front Oncol; 2022 May 11; 12():833816. PubMed ID: 35433460
    [Abstract] [Full Text] [Related]

  • 33. Auto-segmentation of important centers of growth in the pediatric skeleton to consider during radiation therapy based on deep learning.
    Qiu W, Zhang W, Ma X, Kong Y, Shi P, Fu M, Wang D, Hu M, Zhou X, Dong Q, Zhou Q, Zhu J.
    Med Phys; 2023 Jan 11; 50(1):284-296. PubMed ID: 36047281
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  • 34.
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  • 35. Automated segmentation in pelvic radiotherapy: A comprehensive evaluation of ATLAS-, machine learning-, and deep learning-based models.
    Bordigoni B, Trivellato S, Pellegrini R, Meregalli S, Bonetto E, Belmonte M, Castellano M, Panizza D, Arcangeli S, De Ponti E.
    Phys Med; 2024 Sep 11; 125():104486. PubMed ID: 39098106
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  • 36.
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  • 37. 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
    [Abstract] [Full Text] [Related]

  • 38. Enhancing the Contouring Efficiency for Head and Neck Cancer Radiotherapy Using Atlas-based Auto-segmentation and Scripting.
    Nagayasu Y, Ohira S, Ikawa T, Masaoka A, Kanayama N, Nishi T, Kazunori T, Yoshino Y, Miyazaki M, Ueda Y, Konishi K.
    In Vivo; 2024 Jul 22; 38(4):1712-1718. PubMed ID: 38936930
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