These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

513 related articles for article (PubMed ID: 35094405)

  • 21. Long term experience with 3D image guided brachytherapy and clinical outcome in cervical cancer patients.
    Ribeiro I; Janssen H; De Brabandere M; Nulens A; De Bal D; Vergote I; Van Limbergen E
    Radiother Oncol; 2016 Sep; 120(3):447-454. PubMed ID: 27157510
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Evaluation of auto-segmentation for EBRT planning structures using deep learning-based workflow on cervical cancer.
    Wang J; Chen Y; Xie H; Luo L; Tang Q
    Sci Rep; 2022 Aug; 12(1):13650. PubMed ID: 35953516
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Dynamics of High Risk Clinical Target Volume reduction during Brachytherapy and impact on its coverage in patients with inoperable cervical cancer.
    Pobijakova M; Scepanovic D; Paluga M; Fekete M; Mardiak J
    Neoplasma; 2018 Mar; 65(3):425-430. PubMed ID: 29788726
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Attention 3D U-NET for dose distribution prediction of high-dose-rate brachytherapy of cervical cancer: Direction modulated brachytherapy tandem applicator.
    Gautam S; Osman AFI; Richeson D; Gholami S; Manandhar B; Alam S; Song WY
    Med Phys; 2024 Aug; 51(8):5593-5603. PubMed ID: 38830129
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Automatic segmentation of high-risk clinical target volume and organs at risk in brachytherapy of cervical cancer with a convolutional neural network.
    Zhu J; Yan J; Zhang J; Yu L; Song A; Zheng Z; Chen Y; Wang S; Chen Q; Liu Z; Zhang F
    Cancer Radiother; 2024 Aug; 28(4):354-364. PubMed ID: 39147623
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Automatic segmentation and applicator reconstruction for CT-based brachytherapy of cervical cancer using 3D convolutional neural networks.
    Zhang D; Yang Z; Jiang S; Zhou Z; Meng M; Wang W
    J Appl Clin Med Phys; 2020 Oct; 21(10):158-169. PubMed ID: 32991783
    [TBL] [Abstract][Full Text] [Related]  

  • 27. 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]  

  • 28. Fully automated segmentation of clinical target volume in cervical cancer from magnetic resonance imaging with convolutional neural network.
    Zabihollahy F; Viswanathan AN; Schmidt EJ; Lee J
    J Appl Clin Med Phys; 2022 Sep; 23(9):e13725. PubMed ID: 35894782
    [TBL] [Abstract][Full Text] [Related]  

  • 29. 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]  

  • 30. Deep learning-based segmentation for high-dose-rate brachytherapy in cervical cancer using 3D Prompt-ResUNet.
    Xue X; Sun L; Liang D; Zhu J; Liu L; Sun Q; Liu H; Gao J; Fu X; Ding J; Dai X; Tao L; Cheng J; Li T; Zhou F
    Phys Med Biol; 2024 Sep; 69(19):. PubMed ID: 39270708
    [No Abstract]   [Full Text] [Related]  

  • 31. High-risk CTV delineation for cervix brachytherapy: Application of GEC-ESTRO guidelines in Australia and New Zealand.
    Vinod SK; Lim K; Bell L; Veera J; Ohanessian L; Juresic E; Borok N; Chan P; Chee R; Do V; Govindarajulu G; Sridharan S; Johnson C; Moses D; Van Dyk S; Holloway L
    J Med Imaging Radiat Oncol; 2017 Feb; 61(1):133-140. PubMed ID: 27527506
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Deep learning-based ultrasound auto-segmentation of the prostate with brachytherapy implanted needles.
    Hampole P; Harding T; Gillies D; Orlando N; Edirisinghe C; Mendez LC; D'Souza D; Velker V; Correa R; Helou J; Xing S; Fenster A; Hoover DA
    Med Phys; 2024 Apr; 51(4):2665-2677. PubMed ID: 37888789
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Novel use of ViewRay MRI guidance for high-dose-rate brachytherapy in the treatment of cervical cancer.
    Ko HC; Huang JY; Miller JR; Das RK; Wallace CR; De Costa AA; Francis DM; Straub MR; Anderson BM; Bradley KA
    Brachytherapy; 2018; 17(4):680-688. PubMed ID: 29773331
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Comparison of dosimetric parameters in the treatment planning of magnetic resonance imaging-based intracavitary image-guided adaptive brachytherapy with and without optimization using the central shielding technique.
    Nishikawa R; Yoshida K; Ebina Y; Omoteda M; Miyawaki D; Ishihara T; Ejima Y; Akasaka H; Satoh H; Kyotani K; Takahashi S; Sasaki R
    J Radiat Res; 2018 May; 59(3):316-326. PubMed ID: 29518234
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Dose escalation in brachytherapy for cervical cancer: impact on (or increased need for) MRI-guided plan optimisation.
    Paton AM; Chalmers KE; Coomber H; Cameron AL
    Br J Radiol; 2012 Dec; 85(1020):e1249-55. PubMed ID: 23175490
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Comparison of dose-volume analysis between standard Manchester plan and magnetic resonance image-based plan of intracavitary brachytherapy for uterine cervical cancer.
    Takenaka T; Yoshida K; Tachiiri S; Yamazaki H; Aramoto K; Furuya S; Yoshida M; Ban C; Tanaka E; Honda K
    J Radiat Res; 2012 Sep; 53(5):791-7. PubMed ID: 22843369
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Direct sagittal image registration and tumor delineation on sagittal magnetic resonance imaging sequences for image-guided brachytherapy of cervical cancer.
    Radawski JD; Huang Z; Wang JZ; Yuh WT; Mayr NA
    Discov Med; 2012 Jan; 13(68):47-56. PubMed ID: 22284783
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Generalizability of deep learning in organ-at-risk segmentation: A transfer learning study in cervical brachytherapy.
    Ni R; Han K; Haibe-Kains B; Rink A
    Radiother Oncol; 2024 Aug; 197():110332. PubMed ID: 38763356
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Radiobiological optimization comparison between pulse-dose-rate and high-dose-rate brachytherapy in patients with locally advanced cervical cancer.
    Annede P; Dumas I; Schernberg A; Tailleur A; Fumagalli I; Bockel S; Mignot F; Kissel M; Deutsch E; Haie-Meder C; Chargari C
    Brachytherapy; 2019; 18(3):370-377. PubMed ID: 30797698
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Intra-fractional dosimetric analysis of image-guided intracavitary brachytherapy of cervical cancer.
    Yan J; Zhu J; Chen K; Yu L; Zhang F
    Radiat Oncol; 2021 Aug; 16(1):144. PubMed ID: 34348758
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 26.