BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

317 related articles for article (PubMed ID: 37248490)

  • 1. Deep learning for segmentation of the cervical cancer gross tumor volume on magnetic resonance imaging for brachytherapy.
    Rodríguez Outeiral R; González PJ; Schaake EE; van der Heide UA; Simões R
    Radiat Oncol; 2023 May; 18(1):91. PubMed ID: 37248490
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automatic segmentation of magnetic resonance images for high-dose-rate cervical cancer brachytherapy using deep learning.
    Yoganathan SA; Paul SN; Paloor S; Torfeh T; Chandramouli SH; Hammoud R; Al-Hammadi N
    Med Phys; 2022 Mar; 49(3):1571-1584. PubMed ID: 35094405
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Neural network-assisted automated image registration for MRI-guided adaptive brachytherapy in cervical cancer.
    Ecker S; Zimmermann L; Heilemann G; Niatsetski Y; Schmid M; Sturdza AE; Knoth J; Kirisits C; Nesvacil N
    Z Med Phys; 2022 Nov; 32(4):488-499. PubMed ID: 35570099
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Gross tumor volume segmentation for head and neck cancer radiotherapy using deep dense multi-modality network.
    Guo Z; Guo N; Gong K; Zhong S; Li Q
    Phys Med Biol; 2019 Oct; 64(20):205015. PubMed ID: 31514173
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Evaluation of auto-segmentation for brachytherapy of postoperative cervical cancer using deep learning-based workflow.
    Wang J; Chen Y; Tu Y; Xie H; Chen Y; Luo L; Zhou P; Tang Q
    Phys Med Biol; 2023 Feb; 68(5):. PubMed ID: 36753762
    [No Abstract]   [Full Text] [Related]  

  • 8. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Deep Learning using Pre-Brachytherapy MRI to Automatically Predict Applicator Induced Complex Uterine Deformation.
    Ghosh S; Punithakumar K; Huang F; Menon G; Boulanger P
    Annu Int Conf IEEE Eng Med Biol Soc; 2022 Jul; 2022():3826-3829. PubMed ID: 36086328
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Automatic prostate segmentation using deep learning on clinically diverse 3D transrectal ultrasound images.
    Orlando N; Gillies DJ; Gyacskov I; Romagnoli C; D'Souza D; Fenster A
    Med Phys; 2020 Jun; 47(6):2413-2426. PubMed ID: 32166768
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Correlation between the treated volume, the GTV and the CTV at the time of brachytherapy and the histopathologic findings in 33 patients with operable cervix carcinoma.
    Muschitz S; Petrow P; Briot E; Petit C; De Crevoisier R; Duvillard P; Morice P; Haie-Meder C
    Radiother Oncol; 2004 Nov; 73(2):187-94. PubMed ID: 15542166
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automatic Segmentation Using Deep Learning to Enable Online Dose Optimization During Adaptive Radiation Therapy of Cervical Cancer.
    Rigaud B; Anderson BM; Yu ZH; Gobeli M; Cazoulat G; Söderberg J; Samuelsson E; Lidberg D; Ward C; Taku N; Cardenas C; Rhee DJ; Venkatesan AM; Peterson CB; Court L; Svensson S; Löfman F; Klopp AH; Brock KK
    Int J Radiat Oncol Biol Phys; 2021 Mar; 109(4):1096-1110. PubMed ID: 33181248
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Automatic gross tumor segmentation of canine head and neck cancer using deep learning and cross-species transfer learning.
    Groendahl AR; Huynh BN; Tomic O; Søvik Å; Dale E; Malinen E; Skogmo HK; Futsaether CM
    Front Vet Sci; 2023; 10():1143986. PubMed ID: 37026102
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. 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]  

  • 17. 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]  

  • 18. Apparent diffusion coefficients in GEC ESTRO target volumes for image guided adaptive brachytherapy of locally advanced cervical cancer.
    Haack S; Pedersen EM; Jespersen SN; Kallehauge JF; Lindegaard JC; Tanderup K
    Acta Oncol; 2010 Oct; 49(7):978-83. PubMed ID: 20831485
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automatic segmentation of high-risk clinical target volume for tandem-and-ovoids brachytherapy patients using an asymmetric dual-path convolutional neural network.
    Cao Y; Vassantachart A; Ragab O; Bian S; Mitra P; Xu Z; Gallogly AZ; Cui J; Shen ZL; Balik S; Gribble M; Chang EL; Fan Z; Yang W
    Med Phys; 2022 Mar; 49(3):1712-1722. PubMed ID: 35080018
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 16.