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 *

272 related articles for article (PubMed ID: 35533205)

  • 1. 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]  

  • 2. 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]  

  • 3. 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]  

  • 4. 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]  

  • 5. 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]  

  • 6. Delineation of clinical target volume and organs at risk in cervical cancer radiotherapy by deep learning networks.
    Tian M; Wang H; Liu X; Ye Y; Ouyang G; Shen Y; Li Z; Wang X; Wu S
    Med Phys; 2023 Oct; 50(10):6354-6365. PubMed ID: 37246619
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. 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]  

  • 9. Patient-specific transfer learning for auto-segmentation in adaptive 0.35 T MRgRT of prostate cancer: a bi-centric evaluation.
    Kawula M; Hadi I; Nierer L; Vagni M; Cusumano D; Boldrini L; Placidi L; Corradini S; Belka C; Landry G; Kurz C
    Med Phys; 2023 Mar; 50(3):1573-1585. PubMed ID: 36259384
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A dual deep neural network for auto-delineation in cervical cancer radiotherapy with clinical validation.
    Nie S; Wei Y; Zhao F; Dong Y; Chen Y; Li Q; Du W; Li X; Yang X; Li Z
    Radiat Oncol; 2022 Nov; 17(1):182. PubMed ID: 36380378
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Dual convolution-transformer UNet (DCT-UNet) for organs at risk and clinical target volume segmentation in MRI for cervical cancer brachytherapy.
    Kim G; Viswanathan AN; Bhatia R; Landman Y; Roumeliotis M; Erickson B; Schmidt EJ; Lee J
    Phys Med Biol; 2024 Oct; 69(21):. PubMed ID: 39378904
    [No Abstract]   [Full Text] [Related]  

  • 12. 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]  

  • 13. Automatic contouring system for cervical cancer using convolutional neural networks.
    Rhee DJ; Jhingran A; Rigaud B; Netherton T; Cardenas CE; Zhang L; Vedam S; Kry S; Brock KK; Shaw W; O'Reilly F; Parkes J; Burger H; Fakie N; Trauernicht C; Simonds H; Court LE
    Med Phys; 2020 Nov; 47(11):5648-5658. PubMed ID: 32964477
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. 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]  

  • 16. 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]  

  • 17. 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]  

  • 18. Development and validation of a deep learning algorithm for auto-delineation of clinical target volume and organs at risk in cervical cancer radiotherapy.
    Liu Z; Liu X; Guan H; Zhen H; Sun Y; Chen Q; Chen Y; Wang S; Qiu J
    Radiother Oncol; 2020 Dec; 153():172-179. PubMed ID: 33039424
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. A prior-information-based automatic segmentation method for the clinical target volume in adaptive radiotherapy of cervical cancer.
    Wang X; Chang Y; Pei X; Xu XG
    J Appl Clin Med Phys; 2024 May; 25(5):e14350. PubMed ID: 38546277
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 14.