Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Narisu Bai"'
Autor:
Chupeng Zhang, Xuming Chen, Tingfeng Chen, Narisu Bai, Kun Han, Shanlin Sun, Qian Huang, Zhipeng Lu, Xiaohui Xie, Guoqi Zhao, Qianqian Liu, Yong Liu, Yi Xu, Shengyu Yao, Hao Tang
Publikováno v:
Radiotherapy and Oncology. 160:175-184
Background and purpose Delineating organs at risk (OARs) on computed tomography (CT) images is an essential step in radiation therapy; however, it is notoriously time-consuming and prone to inter-observer variation. Herein, we report a deep learning-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::04b7db6a31a933f09279486031e2357b
https://doi.org/10.1016/j.radonc.2021.04.019
https://doi.org/10.1016/j.radonc.2021.04.019
Publikováno v:
ISBI
Organs-at-risk (OAR) delineation in computed tomography (CT) is an important step in Radiation Therapy (RT) planning. Recently, deep learning based methods for OAR delineation have been proposed and applied in clinical practice for separate regions o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b2a015938ee5d75bb23ff7057224844a
http://arxiv.org/abs/2001.04446
http://arxiv.org/abs/2001.04446
Autor:
Yong Liu, Kun Han, Xiaohui Xie, Hao Tang, Xuming Chen, Xingwei Liu, Shanlin Sun, Huang Qian, Narisu Bai
Publikováno v:
WACV
Multi-organ segmentation is one of most successful applications of deep learning in medical image analysis. Deep convolutional neural nets (CNNs) have shown great promise in achieving clinically applicable image segmentation performance on CT or MRI
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9e4d7440d2b810db3c8810d883fceb8f
Publikováno v:
SCIENTIA SINICA Physica, Mechanica & Astronomica. 45:086801-086801
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d144692b6a8cb4d71d5c08fa3ac8d6dc
https://doi.org/10.1360/sspma2015-00074
https://doi.org/10.1360/sspma2015-00074