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
  • [41] multimodal imaging in protontherapy: accuracy in contouring of organs at risk in skull base chordoma
    Anemoni, Luca
    Imparato, Sara
    Iannalfi, Alberto
    Riva, Giulia
    Ciccone, Lucia Pia
    Orlandi, Ester
    Preda, Lorenzo
    Paganelli, Chiara
    Morelli, Letizia
    Tampellini, Sara
    Piazzolla, Maria Elena
    RADIOTHERAPY AND ONCOLOGY, 2024, 194 : S5990 - S5992
  • [42] Deep learning-assisted interactive contouring of lung cancer: Impact on contouring time and consistency
    Trimpl, Michael J.
    Campbell, Sorcha
    Panakis, Niki
    Ajzensztejn, Daniel
    Burke, Emma
    Ellis, Shawn
    Johnstone, Philippa
    Doyle, Emma
    Towers, Rebecca
    Higgins, Geoffrey
    Bernard, Claire
    Hustinx, Roland
    Vallis, Katherine A.
    Stride, Eleanor P. J.
    Gooding, Mark J.
    RADIOTHERAPY AND ONCOLOGY, 2024, 200
  • [43] Artificial intelligence contouring in radiotherapy for organs-at-risk and lymph node areas
    Meyer, Celine
    Huger, Sandrine
    Bruand, Marie
    Leroy, Thomas
    Palisson, Jeremy
    Retif, Paul
    Sarrade, Thomas
    Barateau, Anais
    Renard, Sophie
    Jolnerovski, Maria
    Demogeot, Nicolas
    Marcel, Johann
    Martz, Nicolas
    Stefani, Anais
    Sellami, Selima
    Jacques, Juliette
    Agnoux, Emma
    Gehin, William
    Trampetti, Ida
    Margulies, Agathe
    Golfier, Constance
    Khattabi, Yassir
    Olivier, Cravereau
    Alizee, Renan
    Py, Jean-Francois
    Faivre, Jean-Christophe
    RADIATION ONCOLOGY, 2024, 19 (01)
  • [44] A Novel Tool to Assess Contouring Accuracy of Organs-at-Risk in Stereotactic Radiosurgery
    Stang, K.
    Guenther, E.
    Kozel, Z.
    Rusu, I. A.
    Siddiqui, Z.
    Melian, E.
    Sethi, A.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2015, 93 (03): : S158 - S159
  • [45] Interobserver Contouring Variability in Stereotactic Radiosurgery: Dose Implications for Organs-a- Risk
    Guenther, E.
    Stang, K.
    Kozel, Z.
    Rusu, I. A.
    Melian, E.
    Sethi, A.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2015, 93 (03): : E588 - E589
  • [46] COMPUTERIZED RE-CONTOURING OF H&N ORGANS AT RISK IS A USEFUL ALTERNATIVE TO PHYSICIAN RE-CONTOURING
    Brouwer, C. L.
    Meertens, H.
    Bijl, H. P.
    Chouvalova, O.
    Burlage, F.
    Steenbakkers, R.
    Langendijk, J.
    van't Veld, A.
    RADIOTHERAPY AND ONCOLOGY, 2010, 96 : S173 - S173
  • [47] A deep learning segmentation method to assess dose to organs at risk during breast radiotherapy
    Saha, Monjoy
    Jung, Jae Won
    Lee, Sung-Woo
    Lee, Choonik
    Lee, Choonsik
    Mille, Matthew M.
    PHYSICS & IMAGING IN RADIATION ONCOLOGY, 2023, 28
  • [48] The dosimetric impact of deep learning-based organs at risk auto-segmentation
    Guo, H.
    Xia, X.
    Zhong, Y.
    Peng, J.
    Hu, W.
    Wang, J.
    Zhang, Z.
    RADIOTHERAPY AND ONCOLOGY, 2021, 161 : S1370 - S1371
  • [49] Segmentation of the Prostate and Organs at Risk in Male Pelvic CT Images Using Deep Learning
    Kazemilar, S.
    Balagopal, A.
    Nguyen, D.
    McGuire, S.
    Hannan, R.
    Jiang, S.
    Owrangi, A.
    MEDICAL PHYSICS, 2018, 45 (06) : E688 - E688
  • [50] Clinical evaluation of organs at risk deep learning auto-segmentation for cervix brachytherapy
    Keek, Simon A.
    Mans, Anton
    Nowee, Marlies E.
    Rijkmans, Eva E.
    Schaake, Eva C.
    Simoes, Rita
    Janssen, Tomas M.
    RADIOTHERAPY AND ONCOLOGY, 2024, 194 : S333 - S336
12345