中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共4条，第1-4条 帮助

限定条件            
已选(0)清除 条数/页：   排序方式：
Commissioning and clinical implementation of an Autoencoder based Classification-Regression model for VMAT patient-specific QA in a multi-institution scenario 期刊论文
RADIOTHERAPY AND ONCOLOGY, 2021, 卷号: 161, 期号: 10.1016/j.radonc.2021.06.024, 页码: 230-240
作者:  Yang, Ruijie;  Yang, Xueying;  Wang, Le;  Li, Dingjie;  Guo, Yuexin;  Li, Ying;  Guan, Yumin;  Wu, Xiangyang;  Xu, Shouping;  Zhang, Shuming;  Chan, Maria F.;  Geng, Lisheng;  Sui, Jing
Adobe PDF(2840Kb)  |  收藏  |  浏览/下载：373/60  |  提交时间：2021/11/02
Machine learning  VMAT patient-specific QA  Multi-institution validation  Commissioning  Clinical implementation  
A Novel Adaptive Parameter Search Elastic Net Method for Fluorescent Molecular Tomography 期刊论文
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2021, 卷号: 40, 期号: 5, 页码: 1484-1498
作者:  Wang, Hanfan;  Bian, Chang;  Kong, Lingxin;  An, Yu;  Du, Yang;  Tian, Jie
Adobe PDF(8176Kb)  |  收藏  |  浏览/下载：400/64  |  提交时间：2021/06/15
Image reconstruction  Fluorescence  Probes  Mathematical model  Photonics  Molecular imaging  Biological tissues  Fluorescence molecular tomography  adaptive parameter search  elastic net  
Mixed Metal Metal-Organic Frameworks Derived Carbon Supporting ZnFe2O4/C for High-Performance Magnetic Particle Imaging 期刊论文
NANO LETTERS, 2021, 卷号: 21, 期号: 7, 页码: 2730-2737
作者:  Jiang, Zhenqi;  Han, Xiao;  Du, Yang;  Li, Yanying;  Li, Yong;  Li, Juan;  Tian, Jie;  Wu, Aiguo
收藏  |  浏览/下载：239/0  |  提交时间：2021/06/07
Magnetic Particle Imaging  Metal-Organic Frameworks  High-Temperature Pyrolysis  Esophageal Squamous Cell Cancer  
ImmunoAIzer: A Deep Learning-Based Computational Framework to Characterize Cell Distribution and Gene Mutation in Tumor Microenvironment 期刊论文
CANCERS, 2021, 卷号: 13, 期号: 7, 页码: 21
作者:  Bian, Chang;  Wang, Yu;  Lu, Zhihao;  An, Yu;  Wang, Hanfan;  Kong, Lingxin;  Du, Yang;  Tian, Jie
Adobe PDF(14076Kb)  |  收藏  |  浏览/下载：284/25  |  提交时间：2021/05/17
deep learning  cell distribution  biomarker  tumor gene mutation  tumor microenvironment (TME)  semi-supervised learning  hematoxylin and eosin (H&  E)