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2020 – today
- 2021
[j63]Lei Sun, Yanfang Xue, Yining Zhang, Lishan Qiao, Limei Zhang, Mingxia Liu:
Estimating sparse functional connectivity networks via hyperparameter-free learning model. Artif. Intell. Medicine 111: 102004 (2021)- [j62]Mengting Xu, Tao Zhang, Zhongnian Li, Mingxia Liu, Daoqiang Zhang:
Towards evaluating the robustness of deep diagnostic models by adversarial attack. Medical Image Anal. 69: 101977 (2021) - [j61]Mingliang Wang, Jiashuang Huang, Mingxia Liu, Daoqiang Zhang:
Modeling dynamic characteristics of brain functional connectivity networks using resting-state functional MRI. Medical Image Anal. 71: 102063 (2021) - [j60]Hao Guan
, Yunbi Liu, Erkun Yang, Pew-Thian Yap, Dinggang Shen, Mingxia Liu:
Multi-site MRI harmonization via attention-guided deep domain adaptation for brain disorder identification. Medical Image Anal. 71: 102076 (2021) - [j59]Kelei He, Wei Zhao, Xingzhi Xie, Wen Ji, Mingxia Liu, Zhenyu Tang, Yinghuan Shi, Feng Shi, Yang Gao, Jun Liu, Junfeng Zhang, Dinggang Shen:
Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images. Pattern Recognit. 113: 107828 (2021) - [j58]Shuai Wang, Yang Cong, Hancan Zhu, Xianyi Chen, Liangqiong Qu, Huijie Fan, Qiang Zhang, Mingxia Liu:
Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract. IEEE J. Biomed. Health Informatics 25(2): 514-525 (2021) - [j57]Shuai Wang, Mingxia Liu, Jun Lian, Dinggang Shen:
Boundary Coding Representation for Organ Segmentation in Prostate Cancer Radiotherapy. IEEE Trans. Medical Imaging 40(1): 310-320 (2021) - [j56]Erkun Yang, Mingxia Liu, Dongren Yao, Bing Cao, Chunfeng Lian, Pew-Thian Yap, Dinggang Shen:
Deep Bayesian Hashing With Center Prior for Multi-Modal Neuroimage Retrieval. IEEE Trans. Medical Imaging 40(2): 503-513 (2021) - [j55]Dongren Yao, Jing Sui, Mingliang Wang, Erkun Yang, Yeerfan Jiaerken, Na Luo, Pew-Thian Yap, Mingxia Liu, Dinggang Shen:
A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity. IEEE Trans. Medical Imaging 40(4): 1279-1289 (2021) - [c47]Erkun Yang, Lihong Wang, David C. Steffens, Guy G. Potter, Mingxia Liu:
Deep Factor Regression For Computer-Aided Analysis of Major Depressive Disorders With Structural MRI Data. ISBI 2021: 208-211 - [c46]Hao Guan, Li Wang, Mingxia Liu:
Multi-Source Domain Adaptation via Optimal Transport for Brain Dementia Identification. ISBI 2021: 1514-1517 - [i6]Hao Guan, Mingxia Liu:
Domain Adaptation for Medical Image Analysis: A Survey. CoRR abs/2102.09508 (2021) - [i5]Mengting Xu, Tao Zhang, Zhongnian Li, Mingxia Liu, Daoqiang Zhang:
Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack. CoRR abs/2103.03438 (2021) - 2020
- [j54]Jun Zhang, Mingxia Liu, Li Wang, Si Chen, Peng Yuan, Jianfu Li, Steve Guo-Fang Shen, Zhen Tang, Ken-Chung Chen, James J. Xia, Dinggang Shen:
Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization. Medical Image Anal. 60 (2020) - [j53]Tao Zhou, Kim-Han Thung, Mingxia Liu, Feng Shi, Changqing Zhang, Dinggang Shen:
Multi-modal latent space inducing ensemble SVM classifier for early dementia diagnosis with neuroimaging data. Medical Image Anal. 60 (2020) - [j52]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) - [j51]Mingliang Wang, Xiaoke Hao, Jiashuang Huang, Kangcheng Wang, Li Shen, Xijia Xu, Daoqiang Zhang, Mingxia Liu:
Hierarchical Structured Sparse Learning for Schizophrenia Identification. Neuroinformatics 18(1): 43-57 (2020) - [j50]Chunfeng Lian, Mingxia Liu, Jun Zhang, Dinggang Shen:
Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI. IEEE Trans. Pattern Anal. Mach. Intell. 42(4): 880-893 (2020) - [j49]Mingliang Wang, Chunfeng Lian, Dongren Yao, Daoqiang Zhang, Mingxia Liu, Dinggang Shen:
Spatial-Temporal Dependency Modeling and Network Hub Detection for Functional MRI Analysis via Convolutional-Recurrent Network. IEEE Trans. Biomed. Eng. 67(8): 2241-2252 (2020) - [j48]Wei Shao, Sheng-Jun Huang, Mingxia Liu, Daoqiang Zhang:
Querying Representative and Informative Super-Pixels for Filament Segmentation in Bioimages. IEEE ACM Trans. Comput. Biol. Bioinform. 17(4): 1394-1405 (2020) - [j47]Mingxia Liu, Jun Zhang, Chunfeng Lian, Dinggang Shen:
Weakly Supervised Deep Learning for Brain Disease Prognosis Using MRI and Incomplete Clinical Scores. IEEE Trans. Cybern. 50(7): 3381-3392 (2020) - [j46]Liang Sun, Wei Shao, Mingliang Wang, Daoqiang Zhang, Mingxia Liu:
High-Order Feature Learning for Multi-Atlas Based Label Fusion: Application to Brain Segmentation With MRI. IEEE Trans. Image Process. 29: 2702-2713 (2020) - [j45]Yingkun Hou, Jun Xu, Mingxia Liu, Guanghai Liu, Li Liu, Fan Zhu, Ling Shao:
NLH: A Blind Pixel-Level Non-Local Method for Real-World Image Denoising. IEEE Trans. Image Process. 29: 5121-5135 (2020) - [j44]Zhenghan Fang, Yong Chen, Mingxia Liu, Lei Xiang, Qian Zhang, Qian Wang, Weili Lin, Dinggang Shen:
Erratum to "Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting". IEEE Trans. Medical Imaging 39(2): 543 (2020) - [j43]Mingliang Wang, Daoqiang Zhang, Jiashuang Huang, Pew-Thian Yap, Dinggang Shen, Mingxia Liu:
Identifying Autism Spectrum Disorder With Multi-Site fMRI via Low-Rank Domain Adaptation. IEEE Trans. Medical Imaging 39(3): 644-655 (2020) - [j42]Liang Sun, Wei Shao, Daoqiang Zhang, Mingxia Liu:
Anatomical Attention Guided Deep Networks for ROI Segmentation of Brain MR Images. IEEE Trans. Medical Imaging 39(6): 2000-2012 (2020) - [j41]Yongsheng Pan, Mingxia Liu, Chunfeng Lian, Yong Xia, Dinggang Shen:
Spatially-Constrained Fisher Representation for Brain Disease Identification With Incomplete Multi-Modal Neuroimages. IEEE Trans. Medical Imaging 39(9): 2965-2975 (2020) - [c45]Weida Li, Mingxia Liu, Fang Chen, Daoqiang Zhang:
Graph-Based Decoding Model for Functional Alignment of Unaligned fMRI Data. AAAI 2020: 2653-2660 - [c44]Dongren Yao, Jing Sui, Erkun Yang, Pew-Thian Yap, Dinggang Shen, Mingxia Liu:
Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder Using Resting-State fMRI. MLMI@MICCAI 2020: 1-10 - [c43]Hao Guan, Erkun Yang, Pew-Thian Yap, Dinggang Shen, Mingxia Liu:
Attention-Guided Deep Domain Adaptation for Brain Dementia Identification with Multi-site Neuroimaging Data. DART/DCL@MICCAI 2020: 31-40 - [c42]Hao Guan, Erkun Yang, Li Wang, Pew-Thian Yap, Mingxia Liu, Dinggang Shen:
Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network. MLMI@MICCAI 2020: 111-119 - [c41]Zhenyuan Ning, Yu Zhang, Yongsheng Pan, Tao Zhong, Mingxia Liu, Dinggang Shen:
LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI. MLMI@MICCAI 2020: 170-179 - [c40]Erkun Yang, Dongren Yao, Bing Cao, Hao Guan, Pew-Thian Yap, Dinggang Shen, Mingxia Liu:
Deep Disentangled Hashing with Momentum Triplets for Neuroimage Search. MICCAI (1) 2020: 191-201 - [c39]Chunxiang Feng, Biao Jie, Xintao Ding, Daoqiang Zhang, Mingxia Liu:
Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification. MLMI@MICCAI 2020: 303-311 - [c38]Yunbi Liu, Yongsheng Pan, Wei Yang, Zhenyuan Ning, Ling Yue, Mingxia Liu, Dinggang Shen:
Joint Neuroimage Synthesis and Representation Learning for Conversion Prediction of Subjective Cognitive Decline. MICCAI (7) 2020: 583-592 - [c37]Yunbi Liu, Mingxia Liu, Yuhua Xi, Genggeng Qin, Dinggang Shen, Wei Yang:
Generating Dual-Energy Subtraction Soft-Tissue Images from Chest Radiographs via Bone Edge-Guided GAN. MICCAI (2) 2020: 678-687 - [e4]Mingxia Liu, Pingkun Yan, Chunfeng Lian, Xiaohuan Cao:
Machine Learning in Medical Imaging - 11th International Workshop, MLMI 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 4, 2020, Proceedings. Lecture Notes in Computer Science 12436, Springer 2020, ISBN 978-3-030-59860-0 [contents] - [i4]Weida Li, Mingxia Liu, Daoqiang Zhang:
Nyström Subspace Learning for Large-scale SVMs. CoRR abs/2002.08937 (2020) - [i3]Kelei He, Wei Zhao, Xingzhi Xie, Wen Ji, Mingxia Liu, Zhenyu Tang, Feng Shi, Yang Gao, Jun Liu, Junfeng Zhang, Dinggang Shen:
Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images. CoRR abs/2005.03832 (2020) - [i2]Li Zhang, Mingliang Wang, Mingxia Liu, Daoqiang Zhang:
A Survey on Deep Learning for Neuroimaging-based Brain Disorder Analysis. CoRR abs/2005.04573 (2020)
2010 – 2019
- 2019
- [j40]Mi Wang, Biao Jie, Weixin Bian, Xintao Ding, Wen Zhou, Zhengdong Wang, Mingxia Liu:
Graph-Kernel Based Structured Feature Selection for Brain Disease Classification Using Functional Connectivity Networks. IEEE Access 7: 35001-35011 (2019) - [j39]Mingxia Liu, Xiaoming You, Xingxing Yu, Sheng Liu:
KL Divergence-Based Pheromone Fusion for Heterogeneous Multi-Colony Ant Optimization. IEEE Access 7: 152646-152657 (2019) - [j38]Liang Sun, Chen Zu, Wei Shao, Junye Guang, Daoqiang Zhang, Mingxia Liu:
Reliability-based robust multi-atlas label fusion for brain MRI segmentation. Artif. Intell. Medicine 96: 12-24 (2019) - [j37]Mingliang Wang, Daoqiang Zhang, Dinggang Shen, Mingxia Liu:
Multi-task exclusive relationship learning for alzheimer's disease progression prediction with longitudinal data. Medical Image Anal. 53: 111-122 (2019) - [j36]Jun Zhang, Mingxia Liu, Yi Zhen:
Multimedia analysis for medical applications. Multim. Syst. 25(2): 71-72 (2019) - [j35]Xuyun Wen, Han Zhang, Gang Li, Mingxia Liu, Weiyan Yin, Weili Lin, Jun Zhang, Dinggang Shen:
First-year development of modules and hubs in infant brain functional networks. NeuroImage 185: 222-235 (2019) - [j34]Yu Zhang, Han Zhang, Xiaobo Chen, Mingxia Liu, Xiaofeng Zhu, Seong-Whan Lee, Dinggang Shen:
Strength and similarity guided group-level brain functional network construction for MCI diagnosis. Pattern Recognit. 88: 421-430 (2019) - [j33]Tao Zhou, Kim-Han Thung, Mingxia Liu, Dinggang Shen:
Brain-Wide Genome-Wide Association Study for Alzheimer's Disease via Joint Projection Learning and Sparse Regression Model. IEEE Trans. Biomed. Eng. 66(1): 165-175 (2019) - [j32]Mingxia Liu, Jun Zhang, Ehsan Adeli, Dinggang Shen:
Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis. IEEE Trans. Biomed. Eng. 66(5): 1195-1206 (2019) - [j31]Zhenghan Fang, Yong Chen, Mingxia Liu, Lei Xiang, Qian Zhang, Qian Wang, Weili Lin, Dinggang Shen:
Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting. IEEE Trans. Medical Imaging 38(10): 2375-2388 (2019) - [j30]Tao Zhou, Mingxia Liu, Kim-Han Thung, Dinggang Shen:
Latent Representation Learning for Alzheimer's Disease Diagnosis With Incomplete Multi-Modality Neuroimaging and Genetic Data. IEEE Trans. Medical Imaging 38(10): 2411-2422 (2019) - [c36]Mingliang Wang, Jiashuang Huang, Mingxia Liu, Daoqiang Zhang:
Functional Connectivity Network Analysis with Discriminative Hub Detection for Brain Disease Identification. AAAI 2019: 1198-1205 - [c35]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 - [c34]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 - [c33]Dongren Yao, Mingxia Liu, Mingliang Wang, Chunfeng Lian, Jie Wei, Li Sun, Jing Sui, Dinggang Shen:
Triplet Graph Convolutional Network for Multi-scale Analysis of Functional Connectivity Using Functional MRI. GLMI@MICCAI 2019: 70-78 - [c32]Yongsheng Pan, Mingxia Liu, Chunfeng Lian, Yong Xia, Dinggang Shen:
Disease-Image Specific Generative Adversarial Network for Brain Disease Diagnosis with Incomplete Multi-modal Neuroimages. MICCAI (3) 2019: 137-145 - [c31]Yongsheng Pan, Mingxia Liu, Li Wang, Yong Xia, Dinggang Shen:
Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis. GLMI@MICCAI 2019: 138-146 - [c30]Chunfeng Lian, Mingxia Liu, Li Wang, Dinggang Shen:
End-to-End Dementia Status Prediction from Brain MRI Using Multi-task Weakly-Supervised Attention Network. MICCAI (4) 2019: 158-167 - [c29]Jing Zhang, Mingxia Liu, Yongsheng Pan, Dinggang Shen:
Unsupervised Conditional Consensus Adversarial Network for Brain Disease Identification with Structural MRI. MLMI@MICCAI 2019: 391-399 - [c28]Tao Zhou, Mingxia Liu, Huazhu Fu, Jun Wang, Jianbing Shen, Ling Shao, Dinggang Shen:
Deep Multi-modal Latent Representation Learning for Automated Dementia Diagnosis. MICCAI (4) 2019: 629-638 - [c27]Chunfeng Lian, Li Wang, Tai-Hsien Wu, Mingxia Liu, Francisca Durán, Ching-Chang Ko, Dinggang Shen:
MeshSNet: Deep Multi-scale Mesh Feature Learning for End-to-End Tooth Labeling on 3D Dental Surfaces. MICCAI (6) 2019: 837-845 - [e3]Daoqiang Zhang, Luping Zhou, Biao Jie, Mingxia Liu:
Graph Learning in Medical Imaging - First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11849, Springer 2019, ISBN 978-3-030-35816-7 [contents] - [e2]Heung-Il Suk, Mingxia Liu, Pingkun Yan, Chunfeng Lian:
Machine Learning in Medical Imaging - 10th International Workshop, MLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Proceedings. Lecture Notes in Computer Science 11861, Springer 2019, ISBN 978-3-030-32691-3 [contents] - [i1]Yingkun Hou, Jun Xu, Mingxia Liu, Guanghai Liu, Li Liu, Fan Zhu, Ling Shao:
NLH: A Blind Pixel-level Non-local Method for Real-world Image Denoising. CoRR abs/1906.06834 (2019) - 2018
- [j29]Qi Zhu, Jiuwen Zhu, Mingxia Liu, Xijia Xu, Daoqiang Zhang:
Multi-Region Correlation Based Functional Brain Network for Disease Diagnosis and Cognitive States Detection. IEEE Access 6: 78065-78076 (2018) - [j28]Mingxia Liu, Jun Zhang, Ehsan Adeli, Dinggang Shen:
Landmark-based deep multi-instance learning for brain disease diagnosis. Medical Image Anal. 43: 157-168 (2018) - [j27]Chunfeng Lian, Jun Zhang, Mingxia Liu, Xiaopeng Zong, Sheng-Che Hung, Weili Lin, Dinggang Shen:
Multi-channel multi-scale fully convolutional network for 3D perivascular spaces segmentation in 7T MR images. Medical Image Anal. 46: 106-117 (2018) - [j26]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) - [j25]Wei Shao, Mingxia Liu, Ying-Ying Xu, Hong-Bin Shen, Daoqiang Zhang:
An Organelle Correlation-Guided Feature Selection Approach for Classifying Multi-Label Subcellular Bio-Images. IEEE ACM Trans. Comput. Biol. Bioinform. 15(3): 828-838 (2018) - [j24]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) - [j23]Mingxia Liu, Yue Gao, Pew-Thian Yap, Dinggang Shen:
Multi-Hypergraph Learning for Incomplete Multimodality Data. IEEE J. Biomed. Health Informatics 22(4): 1197-1208 (2018) - [j22]Mingxia Liu, Jun Zhang, Dong Nie, Pew-Thian Yap, Dinggang Shen:
Anatomical Landmark Based Deep Feature Representation for MR Images in Brain Disease Diagnosis. IEEE J. Biomed. Health Informatics 22(5): 1476-1485 (2018) - [j21]Daoqiang Zhang, Jiashuang Huang, Biao Jie, Junqiang Du, Liyang Tu, Mingxia Liu:
Ordinal Pattern: A New Descriptor for Brain Connectivity Networks. IEEE Trans. Medical Imaging 37(7): 1711-1722 (2018) - [c26]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 - [c25]Tao Zhou, Kim-Han Thung, Mingxia Liu, Feng Shi, Changqing Zhang, Dinggang Shen:
Multi-modal Neuroimaging Data Fusion via Latent Space Learning for Alzheimer's Disease Diagnosis. PRIME@MICCAI 2018: 76-84 - [c24]Guannan Li, Mingxia Liu, Quan-Sen Sun, Dinggang Shen, Li Wang:
Early Diagnosis of Autism Disease by Multi-channel CNNs. MLMI@MICCAI 2018: 303-309 - [c23]Zhenghan Fang, Yong Chen, Mingxia Liu, Yiqiang Zhan, Weili Lin, Dinggang Shen:
Deep Learning for Fast and Spatially-Constrained Tissue Quantification from Highly-Undersampled Data in Magnetic Resonance Fingerprinting (MRF). MLMI@MICCAI 2018: 398-405 - [c22]Li Wang, Gang Li, Feng Shi, Xiaohuan Cao, Chunfeng Lian, Dong Nie, Mingxia Liu, Han Zhang, Guannan Li, Zhengwang Wu, Weili Lin, Dinggang Shen:
Volume-Based Analysis of 6-Month-Old Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis. MICCAI (3) 2018: 411-419 - [c21]Yongsheng Pan, Mingxia Liu, Chunfeng Lian, Tao Zhou, Yong Xia, Dinggang Shen:
Synthesizing Missing PET from MRI with Cycle-consistent Generative Adversarial Networks for Alzheimer's Disease Diagnosis. MICCAI (3) 2018: 455-463 - [c20]Mingliang Wang, Daoqiang Zhang, Jiashuang Huang, Dinggang Shen, Mingxia Liu:
Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification. MICCAI (1) 2018: 647-654 - [c19]Yi-Lin Bei, Sai Qiao, Mingxia Liu, Xiaorong Zhu, Qian Zhang:
A Color Image Watermarking Scheme Against Geometric Rotation Attacks Based on HVS and DCT-DWT. SPAC 2018: 343-347 - [e1]Yinghuan Shi, Heung-Il Suk, Mingxia Liu:
Machine Learning in Medical Imaging - 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. Lecture Notes in Computer Science 11046, Springer 2018, ISBN 978-3-030-00918-2 [contents] - 2017
- [j20]Mingxia Liu, Jun Zhang, Xiaochun Guo, Liujuan Cao:
Hypergraph regularized sparse feature learning. Neurocomputing 237: 185-192 (2017) - [j19]Jun Zhang, Qian Wang, Zejun Hu, Mingxia Liu:
Auroral event representation based on the n-ary fusion of multiple oriented energies. Neurocomputing 253: 42-48 (2017) - [j18]Mingxia Liu, Liujuan Cao, Feng Lu, Yi Zhen:
Multimodal media data understanding and analysis. Neurocomputing 259: 1-2 (2017) - [j17]Mingxia Liu, Jun Zhang, Pew-Thian Yap, Dinggang Shen:
View-aligned hypergraph learning for Alzheimer's disease diagnosis with incomplete multi-modality data. Medical Image Anal. 36: 123-134 (2017) - [j16]Bo Cheng, Mingxia Liu, Dinggang Shen, Zuoyong Li, Daoqiang Zhang:
Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer's Disease. Neuroinformatics 15(2): 115-132 (2017) - [j15]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) - [j14]Jun Zhang, Mingxia Liu, Dinggang Shen:
Detecting Anatomical Landmarks From Limited Medical Imaging Data Using Two-Stage Task-Oriented Deep Neural Networks. IEEE Trans. Image Process. 26(10): 4753-4764 (2017) - [j13]Jun Zhang, Mingxia Liu, Le An, Yaozong Gao, Dinggang Shen:
Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images. IEEE J. Biomed. Health Informatics 21(6): 1607-1616 (2017) - [c18]Mingxia Liu, Jun Zhang, Ehsan Adeli, Dinggang Shen:
Deep Multi-task Multi-channel Learning for Joint Classification and Regression of Brain Status. MICCAI (3) 2017: 3-11 - [c17]Yu Zhang, Han Zhang, Xiaobo Chen, Mingxia Liu, Xiaofeng Zhu, Dinggang Shen:
Inter-subject Similarity Guided Brain Network Modeling for MCI Diagnosis. MLMI@MICCAI 2017: 168-175 - [c16]Jun Zhang, Mingxia Liu, Li Wang, Si Chen, Peng Yuan, Jianfu Li, Steve Guo-Fang Shen, Zhen Tang, Ken-Chung Chen, James J. Xia, Dinggang Shen:
Joint Craniomaxillofacial Bone Segmentation and Landmark Digitization by Context-Guided Fully Convolutional Networks. MICCAI (2) 2017: 720-728 - 2016
- [j12]Wei Shao, Mingxia Liu, Daoqiang Zhang:
Human cell structure-driven model construction for predicting protein subcellular location from biological images. Bioinform. 32(1): 114-121 (2016) - [j11]Mingxia Liu, Daoqiang Zhang:
Feature selection with effective distance. Neurocomputing 215: 100-109 (2016) - [j10]Mingxia Liu, Daoqiang Zhang, Songcan Chen, Hui Xue:
Joint Binary Classifier Learning for ECOC-Based Multi-Class Classification. IEEE Trans. Pattern Anal. Mach. Intell. 38(11): 2335-2341 (2016) - [j9]Mingxia Liu, Daoqiang Zhang, Ehsan Adeli, Dinggang Shen:
Inherent Structure-Based Multiview Learning With Multitemplate Feature Representation for Alzheimer's Disease Diagnosis. IEEE Trans. Biomed. Eng. 63(7): 1473-1482 (2016) - [j8]Mingxia Liu, Daoqiang Zhang:
Pairwise Constraint-Guided Sparse Learning for Feature Selection. IEEE Trans. Cybern. 46(1): 298-310 (2016) - [j7]Mingxia Liu, Daoqiang Zhang, Dinggang Shen:
Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment. IEEE Trans. Medical Imaging 35(6): 1463-1474 (2016) - [c15]Yue Gao, Weizhi Nie, Anan Liu, Yuting Su, Qionghai Dai, Le An, Fuhai Chen, Liujuan Cao, Shuilong Dong, Yu De, Zan Gao, Jiayun Hao, Rongrong Ji, Haisheng Li, Mingxia Liu, Lili Pan, Yu Qiu, Liwei Wei, Zhao Wang, Hongjiang Wei, Yuyao Zhang, Jun Zhang, Yan Zhang, Yali Zheng:
3D Object Retrieval with Multimodal Views. 3DOR@Eurographics 2016 - [c14]Biao Jie, Mingxia Liu, Xi Jiang, Daoqiang Zhang:
Sub-network Based Kernels for Brain Network Classification. BCB 2016: 622-629 - [c13]Mingxia Liu, Junqiang Du, Biao Jie, Daoqiang Zhang:
Ordinal Patterns for Connectivity Networks in Brain Disease Diagnosis. MICCAI (1) 2016: 1-9 - [c12]Jun Zhang, Mingxia Liu, Le An, Yaozong Gao, Dinggang Shen:
Landmark-Based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images. MCV/BAMBI@MICCAI 2016: 35-45 - [c11]Le An, Ehsan Adeli, Mingxia Liu, Jun Zhang, Dinggang Shen:
Semi-supervised Hierarchical Multimodal Feature and Sample Selection for Alzheimer's Disease Diagnosis. MICCAI (2) 2016: 79-87 - [c10]Mingxia Liu, Jun Zhang, Pew-Thian Yap, Dinggang Shen:
Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data. MICCAI (1) 2016: 308-316 - [c9]Mingxia Liu, Xiangdong Chen, Wei Xu, Hua Zhang, Xiaohu You, Weiwei Miao:
Grouped pilot reuse for channel estimation in massive MIMO networks. WCSP 2016: 1-5 - 2015
- [j6]Bo Cheng, Mingxia Liu, Daoqiang Zhang, Brent C. Munsell, Dinggang Shen:
Domain Transfer Learning for MCI Conversion Prediction. IEEE Trans. Biomed. Eng. 62(7): 1805-1817 (2015) - [c8]Mingxia Liu, Daoqiang Zhang, Ehsan Adeli-Mosabbeb, Dinggang Shen:
Relationship Induced Multi-atlas Learning for Alzheimer's Disease Diagnosis. MCV@MICCAI 2015: 24-33 - [c7]Bo Cheng, Mingxia Liu, Daoqiang Zhang:
Multimodal Multi-label Transfer Learning for Early Diagnosis of Alzheimer's Disease. MLMI 2015: 238-245 - [c6]Mingxia Liu, Daoqiang Zhang, Dinggang Shen:
Inherent Structure-Guided Multi-view Learning for Alzheimer's Disease and Mild Cognitive Impairment Classification. MLMI 2015: 296-303 - 2014
- [j5]Mingxia Liu, Daoqiang Zhang, Songcan Chen:
Attribute relation learning for zero-shot classification. Neurocomputing 139: 34-46 (2014) - [j4]