Commercial deep learning-based automated treatment planning validation for oropharyngeal cancer

被引：0
|
作者：
Dankers, F. [1 ]
Balasupramaniam, P. [2 ]
Brussee, M. [1 ]
Onderwater, A. [1 ]
de Jong, M. [1 ]
Astreinidou, E. [1 ]
机构：
[1] Leiden Univ, Radiotherapy, Med Ctr, Leiden, Netherlands
[2] Vrije Univ Amsterdam, Fac Sci, Amsterdam, Netherlands
来源：
RADIOTHERAPY AND ONCOLOGY | 2023年 / 182卷
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：
PO-1631
引用
收藏
页码：S1326 / S1327
页数：2
相关论文
共 50 条
  • [1] Validation of deep learning-based CT image reconstruction for treatment planning
    Yasui, Keisuke
    Saito, Yasunori
    Ito, Azumi
    Douwaki, Momoka
    Ogawa, Shuta
    Kasugai, Yuri
    Ooe, Hiromu
    Nagake, Yuya
    Hayashi, Naoki
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [2] Validation of deep learning-based CT image reconstruction for treatment planning
    Keisuke Yasui
    Yasunori Saito
    Azumi Ito
    Momoka Douwaki
    Shuta Ogawa
    Yuri Kasugai
    Hiromu Ooe
    Yuya Nagake
    Naoki Hayashi
    Scientific Reports, 13
  • [3] Clinical implementation of deep learning automated robust IMPT planning for oropharyngeal cancer
    van Bruggen, I.
    van Dijk, M.
    Brinkman, M.
    Holmstrom, M.
    Oldehinkel, E.
    Scandurra, D.
    Langendijk, J.
    Both, S.
    Korevaar, E.
    RADIOTHERAPY AND ONCOLOGY, 2023, 182 : S187 - S188
  • [4] Explainability of deep learning-based HPV status prediction in oropharyngeal cancer
    La Greca, A.
    Marchiori, C.
    Bogowicz, M.
    Barranco-Garcia, J.
    Konukoglu, E.
    Riesterer, O.
    Balermpas, P.
    Malossi, C.
    Guckenberger, M.
    van Timmeren, J. E.
    Tanadini-Lang, S.
    RADIOTHERAPY AND ONCOLOGY, 2022, 170 : S738 - S739
  • [5] A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram
    Jasper Tromp
    David Bauer
    Brian L. Claggett
    Matthew Frost
    Mathias Bøtcher Iversen
    Narayana Prasad
    Mark C. Petrie
    Martin G. Larson
    Justin A. Ezekowitz
    Scott D. Solomon
    Nature Communications, 13
  • [6] A formal validation of a deep learning-based automated workflow for the interpretation of the echocardiogram
    Tromp, Jasper
    Bauer, David
    Claggett, Brian L.
    Frost, Matthew
    Iversen, Mathias Botcher
    Prasad, Narayana
    Petrie, Mark C.
    Larson, Martin G.
    Ezekowitz, Justin A.
    Solomon, Scott D.
    NATURE COMMUNICATIONS, 2022, 13 (01)
  • [7] Clinical implementation of deep learning-based dose prediction for automated planning
    Heikkila, Janne
    Korkalainen, Henri
    Leino, Akseli
    Ahlnas, Johannes
    Kauppila, Minna
    Sinimyrsky, Arthur
    Honkanen, Juuso T. J.
    Seppala, Jan
    Viren, Tuomas
    RADIOTHERAPY AND ONCOLOGY, 2024, 194 : S4504 - S4507
  • [8] Knowledge-based automated planning for oropharyngeal cancer
    Babier, Aaron
    Boutilier, Justin J.
    McNiven, Andrea L.
    Chan, Timothy C. Y.
    MEDICAL PHYSICS, 2018, 45 (07) : 2875 - 2883
  • [9] Knowledge-Based Automated Planning for Oropharyngeal Cancer
    Babier, A.
    Boutilier, J. J.
    McNiven, A. L.
    Chan, T. C. Y.
    MEDICAL PHYSICS, 2017, 44 (06) : 3294 - 3294
  • [10] A systematic review on deep learning-based automated cancer diagnosis models
    Tandon, Ritu
    Agrawal, Shweta
    Rathore, Narendra Pal Singh
    Mishra, Abhinava K.
    Jain, Sanjiv Kumar
    JOURNAL OF CELLULAR AND MOLECULAR MEDICINE, 2024, 28 (06)
12345