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Journal Abstract Search

1360 related items for PubMed ID: 30830685

  • 1. 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
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  • 11. 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
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  • 12. A method of rapid quantification of patient-specific organ doses for CT using deep-learning-based multi-organ segmentation and GPU-accelerated Monte Carlo dose computing.
    Peng Z, Fang X, Yan P, Shan H, Liu T, Pei X, Wang G, Liu B, Kalra MK, Xu XG.
    Med Phys; 2020 Jun; 47(6):2526-2536. PubMed ID: 32155670
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  • 18. Interactive contour delineation of organs at risk in radiotherapy: Clinical evaluation on NSCLC patients.
    Dolz J, Kirişli HA, Fechter T, Karnitzki S, Oehlke O, Nestle U, Vermandel M, Massoptier L.
    Med Phys; 2016 May; 43(5):2569. PubMed ID: 27147367
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