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Biao Jie
Publications
- 2020
- [j17]Biao Jie, Mingxia Liu, Chunfeng Lian, Feng Shi, Dinggang Shen:
Designing weighted correlation kernels in convolutional neural networks for functional connectivity based brain disease diagnosis. Medical Image Anal. 63: 101709 (2020) - 2019
- [j11]Yang Li, Jingyu Liu, Xinqiang Gao, Biao Jie, Minjeong Kim, Pew-Thian Yap, Chong-Yaw Wee, Dinggang Shen:
Multimodal hyper-connectivity of functional networks using functionally-weighted LASSO for MCI classification. Medical Image Anal. 52: 80-96 (2019) - [c18]Zhengdong Wang, Biao Jie, Weixin Bian, Daoqiang Zhang, Dinggang Shen, Mingxia Liu:
Adaptive Thresholding of Functional Connectivity Networks for fMRI-Based Brain Disease Analysis. GLMI@MICCAI 2019: 18-26 - [c17]Zhengdong Wang, Biao Jie, Mi Wang, Chunxiang Feng, Wen Zhou, Dinggang Shen, Mingxia Liu:
Graph-Kernel-Based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification. GLMI@MICCAI 2019: 27-35 - 2018
- [j10]Biao Jie, Mingxia Liu, Dinggang Shen:
Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease. Medical Image Anal. 47: 81-94 (2018) - [j9]Biao Jie, Mingxia Liu, Daoqiang Zhang, Dinggang Shen:
Sub-Network Kernels for Measuring Similarity of Brain Connectivity Networks in Disease Diagnosis. IEEE Trans. Image Process. 27(5): 2340-2353 (2018) - [c16]Biao Jie, Mingxia Liu, Chunfeng Lian, Feng Shi, Dinggang Shen:
Developing Novel Weighted Correlation Kernels for Convolutional Neural Networks to Extract Hierarchical Functional Connectivities from fMRI for Disease Diagnosis. MLMI@MICCAI 2018: 1-9 - 2017
- [j7]Biao Jie, Mingxia Liu, Jun Liu, Daoqiang Zhang, Dinggang Shen:
Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease. IEEE Trans. Biomed. Eng. 64(1): 238-249 (2017) - [c15]Yang Li, Xinqiang Gao, Biao Jie, Pew-Thian Yap, Minjeong Kim, Chong-Yaw Wee, Dinggang Shen:
Multimodal Hyper-connectivity Networks for MCI Classification. MICCAI (1) 2017: 433-441 - 2016
- [j4]Biao Jie, Chong-Yaw Wee, Dinggang Shen, Daoqiang Zhang:
Hyper-connectivity of functional networks for brain disease diagnosis. Medical Image Anal. 32: 84-100 (2016) - 2015
- [c11]Tingting Ye, Chen Zu, Biao Jie, Dinggang Shen, Daoqiang Zhang:
Discriminative Multi-task Feature Selection for Multi-modality Based AD/MCI Classification. PRNI 2015: 45-48 - 2014
- [j2]Yang Li, Chong-Yaw Wee, Biao Jie, Zi-Wen Peng, Dinggang Shen:
Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification. Neuroinformatics 12(3): 455-469 (2014) - [j1]Biao Jie, Daoqiang Zhang, Wei Gao, Qian Wang, Chong-Yaw Wee, Dinggang Shen:
Integration of Network Topological and Connectivity Properties for Neuroimaging Classification. IEEE Trans. Biomed. Eng. 61(2): 576-589 (2014) - [c9]Biao Jie, Dinggang Shen, Daoqiang Zhang:
Brain Connectivity Hyper-Network for MCI Classification. MICCAI (2) 2014: 724-732 - 2013
- [c5]Biao Jie, Daoqiang Zhang, Heung-Il Suk, Chong-Yaw Wee, Dinggang Shen:
Integrating Multiple Network Properties for MCI Identification. MLMI 2013: 9-16 - [c4]Bo Cheng, Daoqiang Zhang, Biao Jie, Dinggang Shen:
Sparse Multimodal Manifold-Regularized Transfer Learning for MCI Conversion Prediction. MLMI 2013: 251-259 - [c3]Biao Jie, Daoqiang Zhang, Bo Cheng, Dinggang Shen:
Manifold Regularized Multi-Task Feature Selection for Multi-Modality Classification in Alzheimer's Disease. MICCAI (1) 2013: 275-283 - [c2]Chong-Yaw Wee, Yang Li, Biao Jie, Zi-Wen Peng, Dinggang Shen:
Identification of MCI Using Optimal Sparse MAR Modeled Effective Connectivity Networks. MICCAI (2) 2013: 319-327 - 2012
- [c1]Biao Jie, Daoqiang Zhang, Chong-Yaw Wee, Dinggang Shen:
Structural Feature Selection for Connectivity Network-Based MCI Diagnosis. MBIA 2012: 175-184
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