文献
J-GLOBAL ID:202202234142802515
整理番号:22A0570390
画像誘導放射線治療のための深い教師なし学習モデルを用いた人間レベル比較可能制御ボリュームマッピング【JST・京大機械翻訳】
Human-level comparable control volume mapping with a deep unsupervised-learning model for image-guided radiation therapy
著者 (11件):
Liang Xiaokun
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Bassenne Maxime
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Hristov Dimitre H.
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Islam Md Tauhidul
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Zhao Wei
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Jia Mengyu
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Zhang Zhicheng
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Gensheimer Michael
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Beadle Beth
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Le Quynh
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
,
Xing Lei
(Department of Radiation Oncology, Stanford University, Stanford, CA, 94305, USA)
資料名:
Computers in Biology and Medicine
(Computers in Biology and Medicine)
巻:
141
ページ:
Null
発行年:
2022年
JST資料番号:
E0858A
ISSN:
0010-4825
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)