Lung Tumor Motion and its Impact on Deep Learning Prediction of Local Recurrence

被引:0
|
作者
Teo, P. T. [1 ]
Randall, J. W. [2 ]
Bajaj, A. [3 ]
Lou, B. [4 ]
Shah, J. [4 ]
Gopalakrishnan, M. [3 ]
Kamen, A. [5 ]
Das, I. J. [3 ]
Abazeed, M. [2 ]
机构
[1] Northwestern Mem Hosp, Dept Radiat Oncol, Chicago, IL 60611 USA
[2] Northwestern Univ, Dept Radiat Oncol, Chicago, IL 60611 USA
[3] Northwestern Univ, Dept Radiat Oncol, Feinberg Sch Med, Chicago, IL 60611 USA
[4] Siemens Healthineers, Malvern, PA USA
[5] Siemens Healthineers, Princeton, NJ USA
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
2277
引用
收藏
页码:E126 / E126
页数:1
相关论文
共 50 条
  • [1] Lung Cancer Recurrence Risk Prediction through Integrated Deep Learning Evaluation
    Huang, Peng
    Illei, Peter B.
    Franklin, Wilbur
    Wu, Pei-Hsun
    Forde, Patrick M.
    Ashrafinia, Saeed
    Hu, Chen
    Khan, Hamza
    Vadvala, Harshna V.
    Shih, Ie-Ming
    Battafarano, Richard J.
    Jacobs, Michael A.
    Kong, Xiangrong
    Lewis, Justine
    Yan, Rongkai
    Chen, Yun
    Housseau, Franck
    Rahmim, Arman
    Fishman, Elliot K.
    Ettinger, David S.
    Pienta, Kenneth J.
    Wirtz, Denis
    Brock, Malcolm, V
    Lam, Stephen
    Gabrielson, Edward
    [J]. CANCERS, 2022, 14 (17)
  • [2] Prediction of Lung Tumor Motion With Measured Breathing Motion
    Tesfamicael, B.
    Lee, T.
    Keppel, C.
    [J]. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2012, 84 (03): : S735 - S735
  • [3] Detection and prediction of lung tumor motion with fluoroscopy
    Chen, QS
    Weinhous, MS
    Greskovich, JF
    Ciezki, JP
    Deibel, FC
    Macklis, RM
    [J]. PROCEEDINGS OF THE 22ND ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4, 2000, 22 : 2128 - 2131
  • [4] A Deep Transfer Learning-Based Radiomics Model for Prediction of Local Recurrence in Laryngeal Cancer
    Jia, Y.
    Qi, X.
    Du, J.
    Chin, R.
    McKenzie, E.
    Sheng, K.
    [J]. MEDICAL PHYSICS, 2020, 47 (06) : E567 - E567
  • [5] SURGERY OF LOCAL RECURRENCE OF MALIGNANT LUNG-TUMOR
    DOBROVOLSKY, SR
    GRIGORYEVA, SP
    [J]. KHIRURGIYA, 1993, (06): : 60 - 68
  • [6] Learning Local Features of Motion Chain for Human Motion Prediction
    Liu, Zhuoran
    Chen, Lianggangxu
    Li, Chen
    Wang, Changbo
    He, Gaoqi
    [J]. ADVANCES IN COMPUTER GRAPHICS, CGI 2023, PT III, 2024, 14497 : 40 - 52
  • [7] A novel panoptic segmentation model for lung tumor prediction using deep learning approaches
    Devi, Koppagiri Jyothsna
    Sudha, S. V.
    [J]. SOFT COMPUTING, 2024, 28 (03) : 2593 - 2604
  • [8] A novel panoptic segmentation model for lung tumor prediction using deep learning approaches
    Koppagiri Jyothsna Devi
    S. V. Sudha
    [J]. Soft Computing, 2024, 28 (3) : 2637 - 2648
  • [9] Prediction of the tumor location in the lung from the skin motion
    Suh, Y
    Yi, B
    Kim, J
    Ahn, S
    Lee, S
    Shin, S
    Choi, E
    [J]. MEDICAL PHYSICS, 2002, 29 (06) : 1240 - 1240
  • [10] ADAPTIVE POLYNOMIAL FILTERS WITH INDIVIDUAL LEARNING RATES FOR COMPUTATIONALLY EFFICIENT LUNG TUMOR MOTION PREDICTION
    Cejnek, Matous
    Bukovsky, Ivo
    Homma, Noriyasu
    Liska, Ondrej
    [J]. 2015 INTERNATIONAL WORKSHOP ON COMPUTATIONAL INTELLIGENCE FOR MULTIMEDIA UNDERSTANDING (IWCIM), 2015,