Zobrazeno 1 - 10
of 128
pro vyhledávání: '"DAI, XIANJIN"'
Autor:
Rajendran, Praveenbalaji, Yang, Yong, Niedermayr, Thomas R., Gensheimer, Michael, Beadle, Beth, Le, Quynh-Thu, Xing, Lei, Dai, Xianjin
Radiation therapy (RT) is one of the most effective treatments for cancer, and its success relies on the accurate delineation of targets. However, target delineation is a comprehensive medical decision that currently relies purely on manual processes
Externí odkaz:
http://arxiv.org/abs/2407.07296
Autor:
Zhang, Yupei, Dai, Xianjin, Tian, Zhen, Lei, Yang, Wynne, Jacob F., Patel, Pretesh, Chen, Yue, Liu, Tian, Yang, Xiaofeng
This study proposed a deep learning-based tracking method for ultrasound (US) image-guided radiation therapy. The proposed cascade deep learning model is composed of an attention network, a mask region-based convolutional neural network (mask R-CNN),
Externí odkaz:
http://arxiv.org/abs/2209.06952
Autor:
Dai, Xianjin, Lei, Yang, Wang, Tonghe, Dhabaan, Anees H., McDonald, Mark, Beitler, Jonathan J., Curran, Walter J., Zhou, Jun, Liu, Tian, Yang, Xiaofeng
Purpose: Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-variability process. We aim to develop a fully automated approach aided
Externí odkaz:
http://arxiv.org/abs/2010.04275
Autor:
Dai, Xianjin, Lei, Yang, Liu, Yingzi, Wang, Tonghe, Ren, Lei, Curran, Walter J., Patel, Pretesh, Liu, Tian, Yang, Xiaofeng
Purpose: Correcting or reducing the effects of voxel intensity non-uniformity (INU) within a given tissue type is a crucial issue for quantitative MRI image analysis in daily clinical practice. In this study, we present a deep learning-based approach
Externí odkaz:
http://arxiv.org/abs/2005.00516
Publikováno v:
In Photoacoustics December 2023 34
Autor:
Zhao, Wei, Lv, Tianling, Gao, Peng, Shen, Liyue, Dai, Xianjin, Cheng, Kai, Jia, Mengyu, Chen, Yang, Xing, Lei
In a standard computed tomography (CT) image, pixels having the same Hounsfield Units (HU) can correspond to different materials and it is, therefore, challenging to differentiate and quantify materials. Dual-energy CT (DECT) is desirable to differen
Externí odkaz:
http://arxiv.org/abs/1906.04874
Publikováno v:
In International Journal of Particle Therapy June 2024 12 Supplement
Akademický článek
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Publikováno v:
In Journal of Virological Methods December 2016 238:6-12
Publikováno v:
In Optics Communications 15 May 2014 319:110-112