Deep Learning Contouring of Thoracic Organs At Risk

被引：0
|
作者：
Peressutti, D. [1 ]
Aljabar, P. [1 ]
van Soest, J. [2 ]
Lustberg, T. [2 ]
van der Stoep, J. [2 ]
Dekker, A. [2 ]
van Elmpt, W. [2 ]
Gooding, M. [1 ]
机构：
[1] Mirada Med Ltd, Sci & Med Technol, Oxford, England
[2] Maastricht Univ, Med Ctr, Dept Radiat Oncol, MAASTRO GROW Sch Oncol Dev Biol, Maastricht, Netherlands
来源：
MEDICAL PHYSICS | 2017年 / 44卷 / 06期
基金：
“创新英国”项目;
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：
TU-FG-605-
引用
收藏
页码：3159 / 3159
页数：1
相关论文
共 50 条
  • [21] Automatic Organ Contouring for Thoracic CT Images with Convolutional Encoder and Decoder Deep Learning Neural Network
    Lam, D.
    McClain, B.
    Sun, B.
    Zhang, T.
    Santanam, L.
    Goddu, S.
    Bradley, J.
    Mutic, S.
    Zhao, T.
    MEDICAL PHYSICS, 2017, 44 (06) : 3148 - 3148
  • [22] Thoracic Organs at Risk (OARs) Contouring Variations and Consensus in Radiation Therapy for Non-Small Cell Lung Cancer
    Liu, J. L.
    Jiang, X.
    Tan, Z.
    Li, Z.
    Wang, Y.
    Xie, Y.
    Cai, J.
    Zhu, G.
    Li, J.
    Xie, C.
    Ma, X.
    Xiao, G.
    Liu, H.
    Ge, H.
    Zhao, J.
    Liang, J.
    Shen, Q.
    Xu, Q.
    Liu, R.
    Zhou, S.
    Zhong, W.
    Kong, W.
    Jiang, Y.
    Xu, Y.
    Fu, Z.
    Liu, Y.
    Zhu, Z.
    Bi, N.
    Yuan, S.
    Zhao, L.
    Song, Q.
    Lu, Y.
    Fu, X. L.
    Wang, L.
    Machtay, M.
    Curran, W.
    Kong, F. M.
    JOURNAL OF THORACIC ONCOLOGY, 2021, 16 (10) : S1047 - S1048
  • [23] Automated CTV Contouring for Prostate and Nodes Utilizing Deep Learning Contouring
    Malesevic, V.
    Potters, L.
    Riegel, A. C.
    Cao, Y.
    Baker, J.
    MEDICAL PHYSICS, 2021, 48 (06)
  • [24] Comparison of different software solutions for automatic contouring of organs at risk
    Bislich, Oliver
    Peters, Sarah
    Exner, Sebastian
    Fehlauer, Fabian
    STRAHLENTHERAPIE UND ONKOLOGIE, 2023, 199 : S171 - S171
  • [25] Interactive contouring through contextual deep learning
    Trimpl, Michael J.
    Boukerroui, Djamal
    Stride, Eleanor P. J.
    Vallis, Katherine A.
    Gooding, Mark J.
    MEDICAL PHYSICS, 2021, 48 (06) : 2951 - 2959
  • [26] Interactive Contouring Through Contextual Deep Learning
    Trimpl, M.
    Boukerroui, D.
    Stride, E.
    Vallis, K.
    Gooding, M.
    MEDICAL PHYSICS, 2020, 47 (06) : E630 - E630
  • [27] Benefits of deep learning for delineation of organs at risk in head and neck cancer
    van der Veen, J.
    Willems, S.
    Deschuymer, S.
    Robben, D.
    Crijns, W.
    Maes, F.
    Nuyts, S.
    RADIOTHERAPY AND ONCOLOGY, 2019, 138 : 68 - 74
  • [28] Benefits of deep learning for delineation of organs at risk in head and neck cancer
    Van der Veen, J.
    Willems, S.
    Robben, D.
    Crijns, W.
    Maes, F.
    Nuyts, S.
    RADIOTHERAPY AND ONCOLOGY, 2019, 133 : S371 - S371
  • [29] Temporal Changes in IMRT Contouring of Organs at Risk for Nasopharyngeal Carcinoma - The Learning Curve Blues and a Tool that Could Help
    Baxi, Siddhartha
    Park, Eileen
    Chong, Vincent
    Chung, Hans T.
    TECHNOLOGY IN CANCER RESEARCH & TREATMENT, 2009, 8 (02) : 131 - 140
  • [30] Clinical evaluation of an interactive deep-learning assisted contouring method for target contouring
    Trimpl, M. J.
    Charlton, P.
    Teoh, S.
    Zeng, H.
    Vallis, K. A.
    Stride, E. J.
    Gooding, M. J.
    RADIOTHERAPY AND ONCOLOGY, 2021, 161 : S966 - S967
12345