Evaluation of an Externally Trained Deep Learning-Based Auto-Segmentation Software in the Process of Artificial Intelligence-Assisted Radiation Treatment Planning for Thoracic Cancers

被引：0
|
作者：
Pan, M. [1 ,2 ]
Serre, L. [2 ,3 ]
Yousuf, J. [2 ]
Hirmiz, K. J. [2 ]
Michie, C. [2 ]
Brown, L. [2 ]
Agapito, J. [2 ,3 ]
机构：
[1] Univ Western Ontario, Schulich Sch Med & Dent, London, ON, Canada
[2] Windsor Reg Hosp Canc Program, Windsor, ON, Canada
[3] Univ Windsor, Windsor, ON, Canada
来源：
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS | 2022年 / 114卷 / 03期
关键词：
D O I：
暂无
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
2223
引用
收藏
页码：E102 / E102
页数：1
相关论文
共 48 条
  • [41] Comparing deep learning-based auto-segmentation of organs at risk and clinical target volumes to expert inter-observer variability in radiotherapy planning
    Wong, Jordan
    Fong, Allan
    McVicar, Nevin
    Smith, Sally
    Giambattista, Joshua
    Wells, Derek
    Kolbeck, Carter
    Giambattista, Jonathan
    Gondara, Lovedeep
    Alexander, Abraham
    RADIOTHERAPY AND ONCOLOGY, 2020, 144 : 152 - 158
  • [42] Comparing Deep Learning-based Auto-segmentation of Organs at Risk and Clinical Target Volumes to Expert Inter-Observer Variability in Radiotherapy Planning
    Wong, J.
    Fong, A.
    McVicar, N.
    Smith, S. L.
    Giambattista, J. A.
    Wells, D. M.
    Lovedeep, G.
    Kolbeck, C.
    Giambattsita, J.
    Alexander, A. S.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2019, 105 (01): : S70 - S71
  • [43] Clinical evaluation of deep learning-based clinical target volume three-channel auto-segmentation algorithm for adaptive radiotherapy in cervical cancer
    Ma, Chen-ying
    Zhou, Ju-ying
    Xu, Xiao-ting
    Qin, Song-bing
    Han, Miao-fei
    Cao, Xiao-huan
    Gao, Yao-zong
    Xu, Lu
    Zhou, Jing-jie
    Zhang, Wei
    Jia, Le-cheng
    BMC MEDICAL IMAGING, 2022, 22 (01)
  • [44] Evaluation of deep learning-based auto-segmentation algorithms for delineating clinical target volume and organs at risk involving data for 125 cervical cancer patients
    Wang, Zhi
    Chang, Yankui
    Peng, Zhao
    Lv, Yin
    Shi, Weijiong
    Wang, Fan
    Pei, Xi
    Xu, X. George
    JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS, 2020, 21 (12): : 272 - 279
  • [45] Quantifying and visualising uncertainty in deep learning-based segmentation for radiation therapy treatment planning: What do radiation oncologists and therapists want?
    Huet-Dastarac, M.
    van Acht, N. M. C.
    Maruccio, F. C.
    van Aalst, J. E.
    van Oorschodt, J. C. J.
    Cnossen, F.
    Janssen, T. M.
    Brouwer, C. L.
    Montero, A. Barragan
    Hurkmans, C. W.
    RADIOTHERAPY AND ONCOLOGY, 2024, 201
  • [46] Evaluation Of A Deep Learning-Based Auto-Segmentation Method For Quality Assurance Of Both Male And Female Pelvic Organ-At-Risk Contours In NCTN Clinical Trials
    Geng, H.
    Men, K.
    Lukka, H.
    Leath, C.
    Kudchadker, R.
    Lee, Y.
    Benedict, S. H.
    Xiao, Y.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2020, 108 (03): : E769 - E769
  • [47] Evaluation of deep learning-based multiparametric MRI oropharyngeal primary tumor auto-segmentation and investigation of input channel effects: Results from a prospective imaging registry
    Wahid, Kareem A.
    Ahmed, Sara
    He, Renjie
    van Dijk, Lisanne, V
    Teuwen, Jonas
    McDonald, Brigid A.
    Salama, Vivian
    Mohamed, Abdallah S. R.
    Salzillo, Travis
    Dede, Cem
    Taku, Nicolette
    Lai, Stephen Y.
    Fuller, Clifton D.
    Naser, Mohamed A.
    CLINICAL AND TRANSLATIONAL RADIATION ONCOLOGY, 2022, 32 : 6 - 14
  • [48] MRI-based 3D models of the hip joint enables radiation-free computer-assisted planning of periacetabular osteotomy for treatment of hip dysplasia using deep learning for automatic segmentation
    Zeng, Guodong
    Schmaranzer, Florian
    Degonda, Celia
    Gerber, Nicolas
    Gerber, Kate
    Tannast, Moritz
    Burger, Juergen
    Siebenrock, Klaus A.
    Zheng, Guoyan
    Lerch, Till D.
    EUROPEAN JOURNAL OF RADIOLOGY OPEN, 2021, 8
12345