CASIA OpenIR

浏览/检索结果: 共3条,第1-3条 帮助

限定条件    
已选(0)清除 条数/页:   排序方式:
Non-invasive radiomics approach potentially predicts non-functioning pituitary adenomas subtypes before surgery 期刊论文
EUROPEAN RADIOLOGY, EUROPEAN RADIOLOGY, 2018, 2018, 卷号: 28, 28, 期号: 9, 页码: 3692-3701, 3692-3701
作者:  Zhang, Shuaitong;  Song, Guidong;  Zang, Yali;  Jia, Jian;  Wang, Chao;  Li, Chuzhong;  Tian, Jie;  Dong, Di;  Zhang, Yazhuo
浏览  |  Adobe PDF(1222Kb)  |  收藏  |  浏览/下载:335/68  |  提交时间:2018/10/10
Non-functioning Pituitary Adenomas  Null Cell Adenomas  Radiomics  Support Vector Machine  Nomograms  Non-functioning Pituitary Adenomas  Null Cell Adenomas  Radiomics  Support Vector Machine  Nomograms  
3D Brain Tumor Segmentation Through Integrating Multiple 2D FCNNs 会议论文
, Quebec City, QC, Canada, 2017-09
作者:  Zhao, Xiaomei;  Wu, Yihong;  Song, Guidong;  Li, Zhenye;  Zhang, Yazhuo;  Fan, Yong
浏览  |  Adobe PDF(1411Kb)  |  收藏  |  浏览/下载:238/61  |  提交时间:2020/05/07
Brain Tumor Segmentation  Fully Convolutional Neural Networks  3d Conditional Random Fields  Multi-views  
A deep learning model integrating FCNNs and CRFs for brain tumor segmentation 期刊论文
MEDICAL IMAGE ANALYSIS, 2018, 卷号: 43, 期号: -, 页码: 98-111
作者:  Zhao, Xiaomei;  Wu, Yihong;  Song, Guidong;  Li, Zhenye;  Zhang, Yazhuo;  Fan, Yong
浏览  |  Adobe PDF(1963Kb)  |  收藏  |  浏览/下载:398/120  |  提交时间:2018/01/04
Brain Tumor Segmentation  Fully Convolutional Neural Networks  Conditional Random Fields  Deep Learning