High-Risk Clinical Target Volume Auto-Contouring on MRI for Cervical Cancer Brachytherapy Using 3D U-Net Transfer Learning

被引:0
|
作者
Barrett, Fletcher
Quirk, Sarah
Souza, Roberto
Stenhouse, Kailyn
Martell, Kevin
Roumeliotis, Michael
McGeachy, Philip
机构
[1] Univ Calgary, Calgary, AB, Canada
[2] Brigham & Womens Hosp, Boston, MA 02115 USA
[3] Johns Hopkins Univ, Baltimore, MD 21218 USA
关键词
D O I
暂无
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
引用
收藏
页码:5799 / 5799
页数:1
相关论文
共 50 条
  • [1] Auto-Contouring of High-Risk Clinical Target Volume and Organ-at-Risks for Cervical Cancer HDR
    Lei, Y.
    Chao, M.
    Yang, K.
    Gupta, V.
    Yoshida, E.
    Wang, T.
    Yang, X.
    Liu, T.
    MEDICAL PHYSICS, 2024, 51 (10) : 7686 - 7686
  • [2] Dwell locations and dwell time prediction of cervical cancer brachytherapy using 3D U-net
    Liu, Tao
    Luo, Rui
    Wen, Shijing
    Wang, Siqi
    Bi, Bin
    Wang, Xianliang
    RADIOTHERAPY AND ONCOLOGY, 2024, 194 : S366 - S367
  • [3] Comparison of MRI and clinical evaluation of cervical cancer -: Significance for target volume definition and organ contouring in brachytherapy
    Dimopoulos, J
    Schard, G
    Kirisits, C
    Lang, S
    Goldner, G
    Wachter, S
    Wachter-Gerstner, N
    Helbich, T
    Pötter, R
    STRAHLENTHERAPIE UND ONKOLOGIE, 2004, 180 : 114 - 115
  • [4] Volumetric Hippocampus Segmentation Using 3D U-Net Based On Transfer Learning
    Widodo, Ramadhan Sanyoto Sugiharso
    Purnama, I. Ketut Eddy
    Rachmadi, Reza Fuad
    2024 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND VIRTUAL ENVIRONMENTS FOR MEASUREMENT SYSTEMS AND APPLICATIONS, CIVEMSA 2024, 2024,
  • [5] Auto Segmentation of Male Pelvis on CBCT Using 3D U-Net
    Qiu, R. L. J.
    Ma, T.
    Stephans, K.
    Shah, C.
    Godley, A.
    Xia, P.
    MEDICAL PHYSICS, 2019, 46 (06) : E138 - E138
  • [6] A 3D Dual Path U-Net of Cancer Segmentation Based on MRI
    He, Yu
    Yu, Xi
    Liu, Chang
    Zhang, Jian
    Hu, Ke
    Zhu, Hong Chao
    2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC), 2018, : 268 - 272
  • [7] Clinical target volume and organs at risk segmentation for rectal cancer radiotherapy using the Flex U-Net network
    Sha, Xue
    Wang, Hui
    Sha, Hui
    Xie, Lu
    Zhou, Qichao
    Zhang, Wei
    Yin, Yong
    FRONTIERS IN ONCOLOGY, 2023, 13
  • [8] Attention 3D U-NET for dose distribution prediction of high-dose-rate brachytherapy of cervical cancer: Direction modulated brachytherapy tandem applicator
    Gautam, Suman
    Osman, Alexander F. I.
    Richeson, Dylan
    Gholami, Somayeh
    Manandhar, Binod
    Alam, Sharmin
    Song, William Y.
    MEDICAL PHYSICS, 2024, 51 (08) : 5593 - 5603
  • [9] 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 RADIOTHERAPIE, 2024, 28 (04): : 354 - 364
  • [10] Patch-based 3D U-Net and transfer learning for longitudinal piglet brain segmentation on MRI
    Coupeau, P.
    Fasquel, J-B
    Mazerand, E.
    Menei, P.
    Montero-Menei, C. N.
    Dinomais, M.
    COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2022, 214