中文版 | English

在结果中检索

CASIA OpenIR

浏览/检索结果: 共92条，第1-10条 帮助

限定条件                
已选(0)清除 条数/页：   排序方式：
A Streamlined 3-D Magnetic Particle Imaging System With a Two-Stage Excitation Feed-Through Compensation Strategy 期刊论文
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2023, 卷号: 72, 页码: 1-10
作者:  Yin L(尹琳);  Li W(李玮);  Bian ZW(卞忠伟);  Chen ZW(陈梓威);  Liu YJ(刘晏君);  Zhong J(钟景);  Zhang SX(张水兴);  Du Y(杜洋);  Hui H(惠辉);  Tian J(田捷)
Adobe PDF(3893Kb)  |  收藏  |  浏览/下载：26/9  |  提交时间：2024/03/26
3-D imaging  compensation strategy  magnetic particle imaging (MPI)  
MSMFN: An ultrasound based multi-step modality fusion network for identifying the histologic subtypes of metastatic cervical lymphadenopathy 期刊论文
IEEE Transactions on Medical Imaging, 2022, 页码: 1-13
作者:  Zheling, Meng;  Yangyang, Zhu;  Wenjing, Pang;  Jie, Tian;  Fang, Nie;  Kun, Wang
Adobe PDF(3049Kb)  |  收藏  |  浏览/下载：258/48  |  提交时间：2023/03/27
Deep learning radiomics of dual-modality ultrasound images for hierarchical diagnosis of unexplained cervical lymphadenopathy 期刊论文
BMC Medicine, 2022, 卷号: 20, 期号: 1, 页码: 1-13
作者:  Zhu,Yangyang;  Meng,Zheling;  Fan,Xiao;  Duan,Yin;  Jia,Yingying;  Dong,Tiantian;  Wang,Yanfang;  Song,Juan;  Tian,Jie;  Wang,Kun;  Nie,Fang
Adobe PDF(3297Kb)  |  收藏  |  浏览/下载：233/34  |  提交时间：2022/09/19
Deep learning  Cervical lymphadenopathy  Ultrasound  Reactive hyperplasia  Tuberculous lymphadenitis  Lymphoma  Metastatic carcinoma  
Deep learning for predicting immunotherapeutic efficacy in advanced non-small cell lung cancer patients: a retrospective study combining progression-free survival risk and overall survival risk 期刊论文
TRANSLATIONAL LUNG CANCER RESEARCH, 2022, 页码: 23
作者:  He, Bing-Xi;  Zhong, Yi-Fan;  Zhu, Yong-Bei;  Deng, Jia-Jun;  Fang, Meng-Jie;  She, Yun-Lang;  Wang, Ting-Ting;  Yang, Yang;  Sun, Xi-Wen;  Belluomini, Lorenzo;  Watanabe, Satoshi;  Dong, Di;  Tian, Jie;  Xie, Dong
Adobe PDF(3742Kb)  |  收藏  |  浏览/下载：316/39  |  提交时间：2022/06/10
Tumor biomarkers  immunotherapy  lung neoplasms  programmed cell death 1 receptor (PD-1 receptor)  biostatistics  
graph convolution based residual connected network for morphological reconstruction in fluorescence molecular tomography 会议论文
, 美国, 2022-2
作者:  Wang Y(王宇);  Bian C(边畅);  Du Y(杜洋);  Tian J(田捷)
Adobe PDF(625Kb)  |  收藏  |  浏览/下载：184/56  |  提交时间：2022/06/14
Fluorescence molecular tomography  Graph convolution network  
Mix Contrast for COVID-19 Mild-to-Critical Prediction 期刊论文
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2021, 卷号: 68, 期号: 12, 页码: 3725-3736
作者:  Zhu, Yongbei;  Wang, Shuo;  Wang, Siwen;  Wu, Qingxia;  Wang, Liusu;  Li, Hongjun;  Wang, Meiyun;  Niu, Meng;  Zha, Yunfei;  Tian, Jie
Adobe PDF(3534Kb)  |  收藏  |  浏览/下载：259/46  |  提交时间：2021/12/28
Coronavirus disease 2019 (COVID-19)  contrastive learning  computed tomography  mixup  prognosis  
基于病理图像的细胞生物标志物表达预测算法研究 学位论文
, 中国科学院自动化研究所: 中国科学院自动化研究所, 2021
作者:  边畅
Adobe PDF(22377Kb)  |  收藏  |  浏览/下载：243/4  |  提交时间：2021/06/21
深度学习，半监督学习，细胞生物标志物，苏木精-伊红染色，多光谱免疫荧光染色，数字病理技术  
A Deep Learning Radiomics Model to Identify Poor Outcome in COVID-19 Patients With Underlying Health Conditions: A Multicenter Study 期刊论文
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2021, 卷号: 25, 期号: 7, 页码: 2353-2362
作者:  Wang, Siwen;  Dong, Di;  Li, Liang;  Li, Hailin;  Bai, Yan;  Hu, Yahua;  Huang, Yuanyi;  Yu, Xiangrong;  Liu, Sibin;  Qiu, Xiaoming;  Lu, Ligong;  Wang, Meiyun;  Zha, Yunfei;  Tian, Jie
Adobe PDF(3142Kb)  |  收藏  |  浏览/下载：254/52  |  提交时间：2021/11/02
COVID-19  deep learning  radiomics  prognosis  computed tomography  
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：269/23  |  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)  
A Computational Prediction Method Based on Modified U-Net for Cell Distribution in Tumor Microenvironment 会议论文
, 线上会议, 2021-2-15
作者:  Bian, Chang;  Wang, Yu;  An, Yu;  Wang, Hanfan;  Du, Yang;  Tian, Jie
Adobe PDF(28768Kb)  |  收藏  |  浏览/下载：184/40  |  提交时间：2021/05/28