BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

232 related articles for article (PubMed ID: 33117694)

  • 21. Applying a novel two-step deep learning network to improve the automatic delineation of esophagus in non-small cell lung cancer radiotherapy.
    Zhang F; Wang Q; Lu N; Chen D; Jiang H; Yang A; Yu Y; Wang Y
    Front Oncol; 2023; 13():1174530. PubMed ID: 37534258
    [TBL] [Abstract][Full Text] [Related]  

  • 22. The impact of organ-at-risk contour variations on automatically generated treatment plans for NSCLC.
    Vaassen F; Hazelaar C; Canters R; Peeters S; Petit S; van Elmpt W
    Radiother Oncol; 2021 Oct; 163():136-142. PubMed ID: 34461185
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Benefits of deep learning for delineation of organs at risk in head and neck cancer.
    van der Veen J; Willems S; Deschuymer S; Robben D; Crijns W; Maes F; Nuyts S
    Radiother Oncol; 2019 Sep; 138():68-74. PubMed ID: 31146073
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Geometric and dosimetric analysis of CT- and MR-based automatic contouring for the EPTN contouring atlas in neuro-oncology.
    Vaassen F; Zegers CML; Hofstede D; Wubbels M; Beurskens H; Verheesen L; Canters R; Looney P; Battye M; Gooding MJ; Compter I; Eekers DBP; van Elmpt W
    Phys Med; 2023 Oct; 114():103156. PubMed ID: 37813050
    [TBL] [Abstract][Full Text] [Related]  

  • 25. 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]  

  • 26. Dosimetric comparison between jaw tracking and static jaw techniques in intensity-modulated radiotherapy.
    Feng Z; Wu H; Zhang Y; Zhang Y; Cheng J; Su X
    Radiat Oncol; 2015 Jan; 10():28. PubMed ID: 25623899
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Dosimetric Impact of Delineation and Motion Uncertainties on the Heart and Substructures in Lung Cancer Radiotherapy.
    Chin V; Finnegan RN; Chlap P; Holloway L; Thwaites DI; Otton J; Delaney GP; Vinod SK
    Clin Oncol (R Coll Radiol); 2024 Jul; 36(7):420-429. PubMed ID: 38649309
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Automatic Segmentation of Clinical Target Volume and Organs-at-Risk for Breast Conservative Radiotherapy Using a Convolutional Neural Network.
    Liu Z; Liu F; Chen W; Tao Y; Liu X; Zhang F; Shen J; Guan H; Zhen H; Wang S; Chen Q; Chen Y; Hou X
    Cancer Manag Res; 2021; 13():8209-8217. PubMed ID: 34754241
    [TBL] [Abstract][Full Text] [Related]  

  • 29. 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; 42(9):5027-34. PubMed ID: 26328953
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Atlas-based auto-segmentation for delineating the heart and cardiac substructures in breast cancer radiation therapy.
    Milo MLH; Nyeng TB; Lorenzen EL; Hoffmann L; Møller DS; Offersen BV
    Acta Oncol; 2022 Feb; 61(2):247-254. PubMed ID: 34427497
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Dosimetric evaluation of synthetic CT for magnetic resonance-only based radiotherapy planning of lung cancer.
    Wang H; Chandarana H; Block KT; Vahle T; Fenchel M; Das IJ
    Radiat Oncol; 2017 Jun; 12(1):108. PubMed ID: 28651599
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Comparison of the automatic segmentation of multiple organs at risk in CT images of lung cancer between deep convolutional neural network-based and atlas-based techniques.
    Zhu J; Zhang J; Qiu B; Liu Y; Liu X; Chen L
    Acta Oncol; 2019 Feb; 58(2):257-264. PubMed ID: 30398090
    [TBL] [Abstract][Full Text] [Related]  

  • 33. RefineNet-based automatic delineation of the clinical target volume and organs at risk for three-dimensional brachytherapy for cervical cancer.
    Jiang X; Wang F; Chen Y; Yan S
    Ann Transl Med; 2021 Dec; 9(23):1721. PubMed ID: 35071415
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Three-dimensional deep neural network for automatic delineation of cervical cancer in planning computed tomography images.
    Ding Y; Chen Z; Wang Z; Wang X; Hu D; Ma P; Ma C; Wei W; Li X; Xue X; Wang X
    J Appl Clin Med Phys; 2022 Apr; 23(4):e13566. PubMed ID: 35192243
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Multi-subject atlas-based auto-segmentation reduces interobserver variation and improves dosimetric parameter consistency for organs at risk in nasopharyngeal carcinoma: A multi-institution clinical study.
    Tao CJ; Yi JL; Chen NY; Ren W; Cheng J; Tung S; Kong L; Lin SJ; Pan JJ; Zhang GS; Hu J; Qi ZY; Ma J; Lu JD; Yan D; Sun Y
    Radiother Oncol; 2015 Jun; 115(3):407-11. PubMed ID: 26025546
    [TBL] [Abstract][Full Text] [Related]  

  • 36. RefineNet-based 2D and 3D automatic segmentations for clinical target volume and organs at risks for patients with cervical cancer in postoperative radiotherapy.
    Xiao C; Jin J; Yi J; Han C; Zhou Y; Ai Y; Xie C; Jin X
    J Appl Clin Med Phys; 2022 Jul; 23(7):e13631. PubMed ID: 35533205
    [TBL] [Abstract][Full Text] [Related]  

  • 37. DVHnet: A deep learning-based prediction of patient-specific dose volume histograms for radiotherapy planning.
    Chen X; Men K; Zhu J; Yang B; Li M; Liu Z; Yan X; Yi J; Dai J
    Med Phys; 2021 Jun; 48(6):2705-2713. PubMed ID: 33550616
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Automatic delineation of organ at risk in cervical cancer radiotherapy based on ensemble learning.
    Cheng T; Zhang Z; Yang X; Lu S; Qian D; Wang X; Zhu H
    Zhong Nan Da Xue Xue Bao Yi Xue Ban; 2022 Aug; 47(8):1058-1064. PubMed ID: 36097773
    [TBL] [Abstract][Full Text] [Related]  

  • 39. A deep learning based automatic segmentation approach for anatomical structures in intensity modulation radiotherapy.
    Zhou H; Li Y; Gu Y; Shen Z; Zhu X; Ge Y
    Math Biosci Eng; 2021 Sep; 18(6):7506-7524. PubMed ID: 34814260
    [TBL] [Abstract][Full Text] [Related]  

  • 40. 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]  

    [Previous]   [Next]    [New Search]
    of 12.