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Intraoperative Imaging-Guided Cancer Surgery: From Current Fluorescence Molecular Imaging Methods to Future Multi-Modality Imaging Technology 期刊论文
THERANOSTICS, 2014, 卷号: 4, 期号: 11, 页码: 1072-1084
作者:  Chi, Chongwei;  Du, Yang;  Ye, Jinzuo;  Kou, Deqiang;  Qiu, Jingdan;  Wang, Jiandong;  Tian, Jie;  Chen, Xiaoyuan
浏览  |  Adobe PDF(826Kb)  |  收藏  |  浏览/下载：318/40  |  提交时间：2015/08/12
Optical Molecular Imaging  Intraoperative Imaging-guided Cancer Surgery  Near-infrared Fluorescence  Multi-modality Imaging  Indocyanine Green  
Gold Nanoshelled Liquid Perfl uorocarbon Nanocapsules for Combined Dual Modal Ultrasound/CT Imaging and Photothermal Therapy of Cancer 期刊论文
SMALL, 2014, 卷号: 10, 期号: 6, 页码: 1220-1227
作者:  Ke, Hengte;  Yue, Xiuli;  Wang, Jinrui;  Xing, Sen;  Zhang, Qian;  Dai, Zhifei;  Tian, Jie;  Wang, Shumin;  Jin, Yushen
浏览  |  Adobe PDF(4442Kb)  |  收藏  |  浏览/下载：240/62  |  提交时间：2015/08/12
Gold Nanoshell  Liquid Perfluorocarbon  Ultrasound Imaging  Ct Imaging  Photothermal Therapy  
Carbon Quantum Dot Stabilized Gadolinium Nanoprobe Prepared via a One-Pot Hydrothermal Approach for Magnetic Resonance and Fluorescence Dual-Modality Bioimaging 期刊论文
ANALYTICAL CHEMISTRY, 2014, 卷号: 86, 期号: 24, 页码: 12122-12129
作者:  Xu, Yang;  Jia, Xiao-Hua;  Yin, Xue-Bo;  He, Xi-Wen;  Zhang, Yu-Kui
Adobe PDF(5793Kb)  |  收藏  |  浏览/下载：403/134  |  提交时间：2015/08/12
A review of EEG and MEG for brainnetome research 期刊论文
COGNITIVE NEURODYNAMICS, 2014, 卷号: 8, 期号: 2, 页码: 87-98
作者:  Zhang, Xin;  Lei, Xu;  Wu, Ting;  Jiang, Tianzi;  Tianzi Jiang
浏览  |  Adobe PDF(391Kb)  |  收藏  |  浏览/下载：282/52  |  提交时间：2015/08/12
Eeg  Meg  Brainnetome  Brain Network  
Interference correction by extracting the information of interference dominant regions: Application to near-infrared spectra 期刊论文
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY, 2014, 卷号: 129, 期号: 129, 页码: 542–550
作者:  Bi, Yiming;  Tang, Liang;  Shan, Peng;  et al.;  Yiming Bi
收藏  |  浏览/下载：204/0  |  提交时间：2015/08/12
Light Scattering interference Correction near-infrared Spectroscopy pre-processing cross-validation