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Journal Abstract Search

302 related items for PubMed ID: 30847761

  • 1. 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; 14(5):745-754. PubMed ID: 30847761
    [Abstract] [Full Text] [Related]

  • 2. 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; 46(2):576-589. PubMed ID: 30480818
    [Abstract] [Full Text] [Related]

  • 3. Fully automatic multi-organ segmentation for head and neck cancer radiotherapy using shape representation model constrained fully convolutional neural networks.
    Tong N, Gou S, Yang S, Ruan D, Sheng K.
    Med Phys; 2018 Oct; 45(10):4558-4567. PubMed ID: 30136285
    [Abstract] [Full Text] [Related]

  • 4. 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
    [Abstract] [Full Text] [Related]

  • 5. Deep convolutional neural network for segmentation of thoracic organs-at-risk using cropped 3D images.
    Feng X, Qing K, Tustison NJ, Meyer CH, Chen Q.
    Med Phys; 2019 May; 46(5):2169-2180. PubMed ID: 30830685
    [Abstract] [Full Text] [Related]

  • 6. 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; 48(12):7757-7772. PubMed ID: 34676555
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  • 8. Training of head and neck segmentation networks with shape prior on small datasets.
    Tappeiner E, Pröll S, Fritscher K, Welk M, Schubert R.
    Int J Comput Assist Radiol Surg; 2020 Sep; 15(9):1417-1425. PubMed ID: 32556921
    [Abstract] [Full Text] [Related]

  • 9. Automatic abdominal multi-organ segmentation using deep convolutional neural network and time-implicit level sets.
    Hu P, Wu F, Peng J, Bao Y, Chen F, Kong D.
    Int J Comput Assist Radiol Surg; 2017 Mar; 12(3):399-411. PubMed ID: 27885540
    [Abstract] [Full Text] [Related]

  • 10. Deep-learning-based detection and segmentation of organs at risk in nasopharyngeal carcinoma computed tomographic images for radiotherapy planning.
    Liang S, Tang F, Huang X, Yang K, Zhong T, Hu R, Liu S, Yuan X, Zhang Y.
    Eur Radiol; 2019 Apr; 29(4):1961-1967. PubMed ID: 30302589
    [Abstract] [Full Text] [Related]

  • 11. 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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  • 14. Interleaved 3D-CNNs for joint segmentation of small-volume structures in head and neck CT images.
    Ren X, Xiang L, Nie D, Shao Y, Zhang H, Shen D, Wang Q.
    Med Phys; 2018 May 27; 45(5):2063-2075. PubMed ID: 29480928
    [Abstract] [Full Text] [Related]

  • 15. 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 27; 47(9):e929-e950. PubMed ID: 32510603
    [Abstract] [Full Text] [Related]

  • 16. Weaving attention U-net: A novel hybrid CNN and attention-based method for organs-at-risk segmentation in head and neck CT images.
    Zhang Z, Zhao T, Gay H, Zhang W, Sun B.
    Med Phys; 2021 Nov 27; 48(11):7052-7062. PubMed ID: 34655077
    [Abstract] [Full Text] [Related]

  • 17. Spatial aggregation of holistically-nested convolutional neural networks for automated pancreas localization and segmentation.
    Roth HR, Lu L, Lay N, Harrison AP, Farag A, Sohn A, Summers RM.
    Med Image Anal; 2018 Apr 27; 45():94-107. PubMed ID: 29427897
    [Abstract] [Full Text] [Related]

  • 18. An application of cascaded 3D fully convolutional networks for medical image segmentation.
    Roth HR, Oda H, Zhou X, Shimizu N, Yang Y, Hayashi Y, Oda M, Fujiwara M, Misawa K, Mori K.
    Comput Med Imaging Graph; 2018 Jun 27; 66():90-99. PubMed ID: 29573583
    [Abstract] [Full Text] [Related]

  • 19. Self-channel-and-spatial-attention neural network for automated multi-organ segmentation on head and neck CT images.
    Gou S, Tong N, Qi S, Yang S, Chin R, Sheng K.
    Phys Med Biol; 2020 Dec 11; 65(24):245034. PubMed ID: 32097892
    [Abstract] [Full Text] [Related]

  • 20. Segmentation of multiple Organs-at-Risk associated with brain tumors based on coarse-to-fine stratified networks.
    Zhao Q, Wang G, Lei W, Fu H, Qu Y, Lu J, Zhang S, Zhang S.
    Med Phys; 2023 Jul 11; 50(7):4430-4442. PubMed ID: 36762594
    [Abstract] [Full Text] [Related]

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