Deep Learning-Based Auto Segmentation Using Generative Adversarial Network On Magnetic Resonance Images for Head and Neck Cancer

被引:0
|
作者
Kawahara, D. [1 ]
Saito, A. [1 ]
Nagata, Y. [1 ]
机构
[1] Dept Radiat Oncol, Hiroshima, Japan
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
SU-F-BRB-0
引用
收藏
页码:E158 / E158
页数:1
相关论文
共 50 条
  • [11] Denoising of magnetic resonance images using discriminative learning-based deep convolutional neural network
    Tripathi, Sumit
    Sharma, Neeraj
    TECHNOLOGY AND HEALTH CARE, 2022, 30 (01) : 145 - 160
  • [12] Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images
    An, Jeehye
    Wendt, Leo
    Wiese, Georg
    Herold, Tom
    Rzepka, Norman
    Mueller, Susanne
    Koch, Stefan Paul
    Hoffmann, Christian J.
    Harms, Christoph
    Boehm-Sturm, Philipp
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [13] Deep learning-based automated lesion segmentation on mouse stroke magnetic resonance images
    Jeehye An
    Leo Wendt
    Georg Wiese
    Tom Herold
    Norman Rzepka
    Susanne Mueller
    Stefan Paul Koch
    Christian J. Hoffmann
    Christoph Harms
    Philipp Boehm-Sturm
    Scientific Reports, 13
  • [14] Deep learning-based segmentation of epithelial ovarian cancer on T2-weighted magnetic resonance images
    Hu, Dingdu
    Jian, Junming
    Li, Yongai
    Gao, Xin
    QUANTITATIVE IMAGING IN MEDICINE AND SURGERY, 2023, 13 (03) : 1464 - +
  • [15] Deep learning-based segmentation of head and neck organs at risk on CBCT images with dosimetric assessment for radiotherapy
    Cubero, Lucia
    Hemon, Cedric
    Barateau, Anais
    Castelli, Joel
    de Crevoisier, Renaud
    Acosta, Oscar
    Pascau, Javier
    PHYSICS IN MEDICINE AND BIOLOGY, 2025, 70 (07):
  • [16] Feasibility Study of a Deep Learning-Based Model Trained On Adults for Auto-Segmentation of Head-And-Neck OARs in Pediatric CT Images
    Shen, Z.
    Olch, A.
    Bai, N.
    Wong, K.
    Chang, E.
    Yang, W.
    MEDICAL PHYSICS, 2022, 49 (06) : E840 - E841
  • [17] Deep Learning-Based Tumor Segmentation of Murine Magnetic Resonance Images of Prostate Cancer Patient-Derived Xenografts
    Nayak, Satvik
    Salkever, Henry
    Diaz, Ernesto
    Sinha, Avantika
    Deveshwar, Nikhil
    Hess, Madeline
    Gibbons, Matthew
    Sahin, Sule
    Rajagopal, Abhejit
    Larson, Peder E. Z.
    Sriram, Renuka
    TOMOGRAPHY, 2025, 11 (03)
  • [18] Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images
    Ren, Jintao
    Teuwen, Jonas
    Nijkamp, Jasper
    Rasmussen, Mathis
    Gouw, Zeno
    Eriksen, Jesper Grau
    Sonke, Jan-Jakob
    Korreman, Stine
    PHYSICS IN MEDICINE AND BIOLOGY, 2024, 69 (16):
  • [19] The impact of training sample size on deep learning-based organ auto-segmentation for head-and-neck patients
    Fang, Yingtao
    Wang, Jiazhou
    Ou, Xiaomin
    Ying, Hongmei
    Hu, Chaosu
    Zhang, Zhen
    Hu, Weigang
    PHYSICS IN MEDICINE AND BIOLOGY, 2021, 66 (18):
  • [20] Infant head and brain segmentation from magnetic resonance images using fusion-based deep learning strategies
    Helena R. Torres
    Bruno Oliveira
    Pedro Morais
    Anne Fritze
    Gabriele Hahn
    Mario Rüdiger
    Jaime C. Fonseca
    João L. Vilaça
    Multimedia Systems, 2024, 30