BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

203 related articles for article (PubMed ID: 37464581)

  • 21. 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; 14(1):213. PubMed ID: 31775825
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Auto-segmentation for total marrow irradiation.
    Watkins WT; Qing K; Han C; Hui S; Liu A
    Front Oncol; 2022; 12():970425. PubMed ID: 36110933
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Automatic multiorgan segmentation in thorax CT images using U-net-GAN.
    Dong X; Lei Y; Wang T; Thomas M; Tang L; Curran WJ; Liu T; Yang X
    Med Phys; 2019 May; 46(5):2157-2168. PubMed ID: 30810231
    [TBL] [Abstract][Full Text] [Related]  

  • 24. A deep learning-based auto-segmentation system for organs-at-risk on whole-body computed tomography images for radiation therapy.
    Chen X; Sun S; Bai N; Han K; Liu Q; Yao S; Tang H; Zhang C; Lu Z; Huang Q; Zhao G; Xu Y; Chen T; Xie X; Liu Y
    Radiother Oncol; 2021 Jul; 160():175-184. PubMed ID: 33961914
    [TBL] [Abstract][Full Text] [Related]  

  • 25. 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; 15(1):104. PubMed ID: 32393280
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Combining natural and artificial intelligence for robust automatic anatomy segmentation: Application in neck and thorax auto-contouring.
    Udupa JK; Liu T; Jin C; Zhao L; Odhner D; Tong Y; Agrawal V; Pednekar G; Nag S; Kotia T; Goodman M; Wileyto EP; Mihailidis D; Lukens JN; Berman AT; Stambaugh J; Lim T; Chowdary R; Jalluri D; Jabbour SK; Kim S; Reyhan M; Robinson CG; Thorstad WL; Choi JI; Press R; Simone CB; Camaratta J; Owens S; Torigian DA
    Med Phys; 2022 Nov; 49(11):7118-7149. PubMed ID: 35833287
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Human factors in the clinical implementation of deep learning-based automated contouring of pelvic organs at risk for MRI-guided radiotherapy.
    Abdulkadir Y; Luximon D; Morris E; Chow P; Kishan AU; Mikaeilian A; Lamb JM
    Med Phys; 2023 Oct; 50(10):5969-5977. PubMed ID: 37646527
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Deep learning-based auto-segmentation of clinical target volumes for radiotherapy treatment of cervical cancer.
    Ma CY; Zhou JY; Xu XT; Guo J; Han MF; Gao YZ; Du H; Stahl JN; Maltz JS
    J Appl Clin Med Phys; 2022 Feb; 23(2):e13470. PubMed ID: 34807501
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Automatic image segmentation based on synthetic tissue model for delineating organs at risk in spinal metastasis treatment planning.
    Wittenstein O; Hiepe P; Sowa LH; Karsten E; Fandrich I; Dunst J
    Strahlenther Onkol; 2019 Dec; 195(12):1094-1103. PubMed ID: 31037351
    [TBL] [Abstract][Full Text] [Related]  

  • 30. 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; 11():638197. PubMed ID: 34026615
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Evaluating Automatic Segmentation for Swallowing-Related Organs for Head and Neck Cancer.
    Li Y; Rao S; Chen W; Azghadi SF; Nguyen KNB; Moran A; Usera BM; Dyer BA; Shang L; Chen Q; Rong Y
    Technol Cancer Res Treat; 2022; 21():15330338221105724. PubMed ID: 35790457
    [No Abstract]   [Full Text] [Related]  

  • 32. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Incremental retraining, clinical implementation, and acceptance rate of deep learning auto-segmentation for male pelvis in a multiuser environment.
    Duan J; Vargas CE; Yu NY; Laughlin BS; Toesca DS; Keole S; Rwigema JCM; Wong WW; Schild SE; Feng X; Chen Q; Rong Y
    Med Phys; 2023 Jul; 50(7):4079-4091. PubMed ID: 37287322
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Self-configuring nnU-Net for automatic delineation of the organs at risk and target in high-dose rate cervical brachytherapy, a low/middle-income country's experience.
    Duprez D; Trauernicht C; Simonds H; Williams O
    J Appl Clin Med Phys; 2023 Aug; 24(8):e13988. PubMed ID: 37042449
    [TBL] [Abstract][Full Text] [Related]  

  • 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; 48(10):5862-5873. PubMed ID: 34342878
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Evaluation of deep learning-based auto-segmentation algorithms for delineating clinical target volume and organs at risk involving data for 125 cervical cancer patients.
    Wang Z; Chang Y; Peng Z; Lv Y; Shi W; Wang F; Pei X; Xu XG
    J Appl Clin Med Phys; 2020 Dec; 21(12):272-279. PubMed ID: 33238060
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Multi-institutional quantitative evaluation and clinical validation of Smart Probabilistic Image Contouring Engine (SPICE) autosegmentation of target structures and normal tissues on computer tomography images in the head and neck, thorax, liver, and male pelvis areas.
    Zhu M; Bzdusek K; Brink C; Eriksen JG; Hansen O; Jensen HA; Gay HA; Thorstad W; Widder J; Brouwer CL; Steenbakkers RJ; Vanhauten HA; Cao JQ; McBrayne G; Patel SH; Cannon DM; Hardcastle N; Tomé WA; Guckenberg M; Parikh PJ
    Int J Radiat Oncol Biol Phys; 2013 Nov; 87(4):809-16. PubMed ID: 24138920
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Prospective Evaluation of Automated Contouring for CT-Based Brachytherapy for Gynecologic Malignancies.
    Kraus AC; Iqbal Z; Cardan RA; Popple RA; Stanley DN; Shen S; Pogue JA; Wu X; Lee K; Marcrom S; Cardenas CE
    Adv Radiat Oncol; 2024 Apr; 9(4):101417. PubMed ID: 38435965
    [TBL] [Abstract][Full Text] [Related]  

  • 39. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Automatic segmentation of the clinical target volume and organs at risk in the planning CT for rectal cancer using deep dilated convolutional neural networks.
    Men K; Dai J; Li Y
    Med Phys; 2017 Dec; 44(12):6377-6389. PubMed ID: 28963779
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 11.