Image with Less Information Watermarking Algorithm Based on DWT. - Yingkun Hou; Xiangcai Zhu; Zhu Lili; Mingxia Liu 001 (SNPD (3), 2007)

The Nonsubsampled Contourlet-Wavelet Hybrid Transform: Design and Application to Image Watermarking. - Yingkun Hou; Chunxia Zhao; Mingxia Liu 001; Deyun Yang (CSSE (3), 2008)

A new approach for texture classification in CBIR. - Shengju Sang; Mingxia Liu 001; Jing Liu; Qi An (Int. J. Comput. Appl. Technol., 2010)

Semisubsampled Wavelet Transform Based Image Watermarking with Strong Robustness to Rotation Attacks. - Yingkun Hou; Chunxia Zhao; Mingxia Liu 001; Zhengli Zhu; Deyun Yang (J. Multim., 2010)

Sparsity Score: A new filter feature selection method based on graph. - Mingxia Liu 001; Dan Sun; Daoqiang Zhang (ICPR, 2012)

Cost-sensitive feature selection with application in software defect prediction. - Linsong Miao; Mingxia Liu 001; Daoqiang Zhang (ICPR, 2012)

Learning Attribute Relation in Attribute-Based Zero-Shot Classification. - Mingxia Liu 001; Songcan Chen; Daoqiang Zhang (IScIDE, 2012)

Attribute relation learning for zero-shot classification. - Mingxia Liu 001; Daoqiang Zhang; Songcan Chen (Neurocomputing, 2014)

Sparsity Score: a Novel Graph-Preserving Feature Selection Method. - Mingxia Liu 001; Daoqiang Zhang (Int. J. Pattern Recognit. Artif. Intell., 2014)

Two-Stage Cost-Sensitive Learning for Software Defect Prediction. - Mingxia Liu 001; Linsong Miao; Daoqiang Zhang (IEEE Trans. Reliab., 2014)

Multimodal Multi-label Transfer Learning for Early Diagnosis of Alzheimer's Disease. - Bo Cheng 006; Mingxia Liu 001; Daoqiang Zhang (MLMI, 2015)

Relationship Induced Multi-atlas Learning for Alzheimer's Disease Diagnosis. - Mingxia Liu 001; Daoqiang Zhang; Ehsan Adeli-Mosabbeb; Dinggang Shen (MCV@MICCAI, 2015)

Inherent Structure-Guided Multi-view Learning for Alzheimer's Disease and Mild Cognitive Impairment Classification. - Mingxia Liu 001; Daoqiang Zhang; Dinggang Shen (MLMI, 2015)

Domain Transfer Learning for MCI Conversion Prediction. - Bo Cheng 006; Mingxia Liu 001; Daoqiang Zhang; Brent C. Munsell; Dinggang Shen (IEEE Trans. Biomed. Eng., 2015)

3D Object Retrieval with Multimodal Views. - Yue Gao 002; Weizhi Nie; Anan Liu; Yuting Su 001; Qionghai Dai; Le An; Fuhai Chen; Liujuan Cao; Shuilong Dong; Yu De; Zan Gao; Jiayun Hao; et al. (3DOR@Eurographics, 2016)

Sub-network Based Kernels for Brain Network Classification. - Biao Jie; Mingxia Liu 001; Xi Jiang 001; Daoqiang Zhang (BCB, 2016)

Semi-supervised Hierarchical Multimodal Feature and Sample Selection for Alzheimer's Disease Diagnosis. - Le An; Ehsan Adeli 001; Mingxia Liu 001; Jun Zhang 018; Dinggang Shen (MICCAI (2), 2016)

Ordinal Patterns for Connectivity Networks in Brain Disease Diagnosis. - Mingxia Liu 001; Junqiang Du; Biao Jie; Daoqiang Zhang (MICCAI (1), 2016)

Diagnosis of Alzheimer's Disease Using View-Aligned Hypergraph Learning with Incomplete Multi-modality Data. - Mingxia Liu 001; Jun Zhang 018; Pew-Thian Yap; Dinggang Shen (MICCAI (1), 2016)

Landmark-Based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images. - Jun Zhang 018; Mingxia Liu 001; Le An; Yaozong Gao; Dinggang Shen (MCV/BAMBI@MICCAI, 2016)

Human cell structure-driven model construction for predicting protein subcellular location from biological images. - Wei Shao 005; Mingxia Liu 001; Daoqiang Zhang (Bioinform., 2016)

Feature selection with effective distance. - Mingxia Liu 001; Daoqiang Zhang (Neurocomputing, 2016)

Joint Binary Classifier Learning for ECOC-Based Multi-Class Classification. - Mingxia Liu 001; Daoqiang Zhang; Songcan Chen; Hui Xue 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2016)

Inherent Structure-Based Multiview Learning With Multitemplate Feature Representation for Alzheimer's Disease Diagnosis. - Mingxia Liu 001; Daoqiang Zhang; Ehsan Adeli 001; Dinggang Shen (IEEE Trans. Biomed. Eng., 2016)

Pairwise Constraint-Guided Sparse Learning for Feature Selection. - Mingxia Liu 001; Daoqiang Zhang (IEEE Trans. Cybern., 2016)

Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment. - Mingxia Liu 001; Daoqiang Zhang; Dinggang Shen (IEEE Trans. Medical Imaging, 2016)

Deep Multi-task Multi-channel Learning for Joint Classification and Regression of Brain Status. - Mingxia Liu 001; Jun Zhang 018; Ehsan Adeli 001; Dinggang Shen (MICCAI (3), 2017)

Joint Craniomaxillofacial Bone Segmentation and Landmark Digitization by Context-Guided Fully Convolutional Networks. - Jun Zhang 018; Mingxia Liu 001; Li Wang 026; Si Chen; Peng Yuan 001; Jianfu Li; Steve Guo-Fang Shen; Zhen Tang; Ken-Chung Chen; James J. Xia; Dinggang Shen (MICCAI (2), 2017)

Inter-subject Similarity Guided Brain Network Modeling for MCI Diagnosis. - Yu Zhang 009; Han Zhang 002; Xiaobo Chen 001; Mingxia Liu 001; Xiaofeng Zhu 001; Dinggang Shen (MLMI@MICCAI, 2017)

Multimodal media data understanding and analysis. - Mingxia Liu 001; Liujuan Cao; Feng Lu; Yi Zhen (Neurocomputing, 2017)

Hypergraph regularized sparse feature learning. - Mingxia Liu 001; Jun Zhang 018; Xiaochun Guo; Liujuan Cao (Neurocomputing, 2017)

Auroral event representation based on the n-ary fusion of multiple oriented energies. - Jun Zhang 018; Qian Wang 019; Zejun Hu; Mingxia Liu 001 (Neurocomputing, 2017)

View-aligned hypergraph learning for Alzheimer's disease diagnosis with incomplete multi-modality data. - Mingxia Liu 001; Jun Zhang 018; Pew-Thian Yap; Dinggang Shen (Medical Image Anal., 2017)

Multi-Domain Transfer Learning for Early Diagnosis of Alzheimer's Disease. - Bo Cheng 006; Mingxia Liu 001; Dinggang Shen; Zuoyong Li; Daoqiang Zhang (Neuroinformatics, 2017)

Temporally Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer's Disease. - Biao Jie; Mingxia Liu 001; Jun Liu 003; Daoqiang Zhang; Dinggang Shen (IEEE Trans. Biomed. Eng., 2017)

Detecting Anatomical Landmarks From Limited Medical Imaging Data Using Two-Stage Task-Oriented Deep Neural Networks. - Jun Zhang 018; Mingxia Liu 001; Dinggang Shen (IEEE Trans. Image Process., 2017)

Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images. - Jun Zhang 018; Mingxia Liu 001; Le An; Yaozong Gao; Dinggang Shen (IEEE J. Biomed. Health Informatics, 2017)

Deep Learning for Fast and Spatially-Constrained Tissue Quantification from Highly-Undersampled Data in Magnetic Resonance Fingerprinting (MRF). - Zhenghan Fang; Yong Chen; Mingxia Liu 001; Yiqiang Zhan; Weili Lin; Dinggang Shen (MLMI@MICCAI, 2018)

Developing Novel Weighted Correlation Kernels for Convolutional Neural Networks to Extract Hierarchical Functional Connectivities from fMRI for Disease Diagnosis. - Biao Jie; Mingxia Liu 001; Chunfeng Lian; Feng Shi 001; Dinggang Shen (MLMI@MICCAI, 2018)

Early Diagnosis of Autism Disease by Multi-channel CNNs. - Guannan Li; Mingxia Liu 001; Quan-Sen Sun; Dinggang Shen; Li Wang 026 (MLMI@MICCAI, 2018)

Synthesizing Missing PET from MRI with Cycle-consistent Generative Adversarial Networks for Alzheimer's Disease Diagnosis. - Yongsheng Pan; Mingxia Liu 001; Chunfeng Lian; Tao Zhou 002; Yong Xia 001; Dinggang Shen (MICCAI (3), 2018)

Volume-Based Analysis of 6-Month-Old Infant Brain MRI for Autism Biomarker Identification and Early Diagnosis. - Li Wang 026; Gang Li 001; Feng Shi 001; Xiaohuan Cao; Chunfeng Lian; Dong Nie; Mingxia Liu 001; Han Zhang 002; Guannan Li; Zhengwang Wu; Weili Lin; Dinggang Shen (MICCAI (3), 2018)

Low-Rank Representation for Multi-center Autism Spectrum Disorder Identification. - Mingliang Wang; Daoqiang Zhang; Jiashuang Huang; Dinggang Shen; Mingxia Liu 001 (MICCAI (1), 2018)

Multi-modal Neuroimaging Data Fusion via Latent Space Learning for Alzheimer's Disease Diagnosis. - Tao Zhou 002; Kim-Han Thung; Mingxia Liu 001; Feng Shi 001; Changqing Zhang; Dinggang Shen (PRIME@MICCAI, 2018)

A Color Image Watermarking Scheme Against Geometric Rotation Attacks Based on HVS and DCT-DWT. - Yi-Lin Bei; Sai Qiao; Mingxia Liu 001; Xiaorong Zhu; Qian Zhang 066 (SPAC, 2018)

Effective Distance based Low Rank Representation for Image Classification. - Ti-Wei Tao; De-Yun Yang; Lin-Lin Wang; Ming-Xia Liu 001 (SPAC, 2018)

Multi-Region Correlation Based Functional Brain Network for Disease Diagnosis and Cognitive States Detection. - Qi Zhu 001; Jiuwen Zhu; Mingxia Liu 001; Xijia Xu; Daoqiang Zhang (IEEE Access, 2018)

Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease. - Biao Jie; Mingxia Liu 001; Dinggang Shen (Medical Image Anal., 2018)

Multi-channel multi-scale fully convolutional network for 3D perivascular spaces segmentation in 7T MR images. - Chunfeng Lian; Jun Zhang 018; Mingxia Liu 001; Xiaopeng Zong; Sheng-Che Hung; Weili Lin; Dinggang Shen (Medical Image Anal., 2018)

Landmark-based deep multi-instance learning for brain disease diagnosis. - Mingxia Liu 001; Jun Zhang 018; Ehsan Adeli 001; Dinggang Shen (Medical Image Anal., 2018)

An Organelle Correlation-Guided Feature Selection Approach for Classifying Multi-Label Subcellular Bio-Images. - Wei Shao 005; Mingxia Liu 001; Ying-Ying Xu; Hong-Bin Shen; Daoqiang Zhang (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

Sub-Network Kernels for Measuring Similarity of Brain Connectivity Networks in Disease Diagnosis. - Biao Jie; Mingxia Liu 001; Daoqiang Zhang; Dinggang Shen (IEEE Trans. Image Process., 2018)

Multi-Hypergraph Learning for Incomplete Multimodality Data. - Mingxia Liu 001; Yue Gao 002; Pew-Thian Yap; Dinggang Shen (IEEE J. Biomed. Health Informatics, 2018)

Anatomical Landmark Based Deep Feature Representation for MR Images in Brain Disease Diagnosis. - Mingxia Liu 001; Jun Zhang 018; Dong Nie; Pew-Thian Yap; Dinggang Shen (IEEE J. Biomed. Health Informatics, 2018)

Ordinal Pattern: A New Descriptor for Brain Connectivity Networks. - Daoqiang Zhang; Jiashuang Huang; Biao Jie; Junqiang Du; Liyang Tu; Mingxia Liu 001 (IEEE Trans. Medical Imaging, 2018)

Functional Connectivity Network Analysis with Discriminative Hub Detection for Brain Disease Identification. - Mingliang Wang; Jiashuang Huang; Mingxia Liu 001; Daoqiang Zhang (AAAI, 2019)

End-to-End Dementia Status Prediction from Brain MRI Using Multi-task Weakly-Supervised Attention Network. - Chunfeng Lian; Mingxia Liu 001; Li Wang 026; Dinggang Shen (MICCAI (4), 2019)

MeshSNet: Deep Multi-scale Mesh Feature Learning for End-to-End Tooth Labeling on 3D Dental Surfaces. - Chunfeng Lian; Li Wang 026; Tai-Hsien Wu; Mingxia Liu 001; Francisca Durán; Ching-Chang Ko; Dinggang Shen (MICCAI (6), 2019)

Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis. - Yongsheng Pan; Mingxia Liu 001; Li Wang 026; Yong Xia 001; Dinggang Shen (GLMI@MICCAI, 2019)

Disease-Image Specific Generative Adversarial Network for Brain Disease Diagnosis with Incomplete Multi-modal Neuroimages. - Yongsheng Pan; Mingxia Liu 001; Chunfeng Lian; Yong Xia 001; Dinggang Shen (MICCAI (3), 2019)

Adaptive Thresholding of Functional Connectivity Networks for fMRI-Based Brain Disease Analysis. - Zhengdong Wang; Biao Jie; Weixin Bian; Daoqiang Zhang; Dinggang Shen; Mingxia Liu 001 (GLMI@MICCAI, 2019)

Graph-Kernel-Based Multi-task Structured Feature Selection on Multi-level Functional Connectivity Networks for Brain Disease Classification. - Zhengdong Wang; Biao Jie; Mi Wang; Chunxiang Feng; Wen Zhou 005; Dinggang Shen; Mingxia Liu 001 (GLMI@MICCAI, 2019)

Triplet Graph Convolutional Network for Multi-scale Analysis of Functional Connectivity Using Functional MRI. - Dongren Yao; Mingxia Liu 001; Mingliang Wang; Chunfeng Lian; Jie Wei; Li Sun; Jing Sui; Dinggang Shen (GLMI@MICCAI, 2019)

Unsupervised Conditional Consensus Adversarial Network for Brain Disease Identification with Structural MRI. - Jing Zhang 010; Mingxia Liu 001; Yongsheng Pan; Dinggang Shen (MLMI@MICCAI, 2019)

Deep Multi-modal Latent Representation Learning for Automated Dementia Diagnosis. - Tao Zhou 002; Mingxia Liu 001; Huazhu Fu; Jun Wang 024; Jianbing Shen; Ling Shao 001; Dinggang Shen (MICCAI (4), 2019)

Graph-Kernel Based Structured Feature Selection for Brain Disease Classification Using Functional Connectivity Networks. - Mi Wang; Biao Jie; Weixin Bian; Xintao Ding; Wen Zhou 005; Zhengdong Wang; Mingxia Liu 001 (IEEE Access, 2019)

Reliability-based robust multi-atlas label fusion for brain MRI segmentation. - Liang Sun 009; Chen Zu; Wei Shao 005; Junye Guang; Daoqiang Zhang; Mingxia Liu 001 (Artif. Intell. Medicine, 2019)

Multi-task exclusive relationship learning for alzheimer's disease progression prediction with longitudinal data. - Mingliang Wang; Daoqiang Zhang; Dinggang Shen; Mingxia Liu 001 (Medical Image Anal., 2019)

Multimedia analysis for medical applications. - Jun Zhang 018; Mingxia Liu 001; Yi Zhen (Multim. Syst., 2019)

First-year development of modules and hubs in infant brain functional networks. - Xuyun Wen; Han Zhang 002; Gang Li 001; Mingxia Liu 001; Weiyan Yin; Weili Lin; Jun Zhang 003; Dinggang Shen (NeuroImage, 2019)

Strength and similarity guided group-level brain functional network construction for MCI diagnosis. - Yu Zhang 009; Han Zhang 002; Xiaobo Chen 001; Mingxia Liu 001; Xiaofeng Zhu 001; Seong-Whan Lee; Dinggang Shen (Pattern Recognit., 2019)

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis. - Mingxia Liu 001; Jun Zhang 018; Ehsan Adeli 001; Dinggang Shen (IEEE Trans. Biomed. Eng., 2019)

Brain-Wide Genome-Wide Association Study for Alzheimer's Disease via Joint Projection Learning and Sparse Regression Model. - Tao Zhou 002; Kim-Han Thung; Mingxia Liu 001; Dinggang Shen (IEEE Trans. Biomed. Eng., 2019)

Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting. - Zhenghan Fang; Yong Chen; Mingxia Liu 001; Lei Xiang; Qian Zhang 066; Qian Wang 001; Weili Lin; Dinggang Shen (IEEE Trans. Medical Imaging, 2019)

Latent Representation Learning for Alzheimer's Disease Diagnosis With Incomplete Multi-Modality Neuroimaging and Genetic Data. - Tao Zhou 002; Mingxia Liu 001; Kim-Han Thung; Dinggang Shen (IEEE Trans. Medical Imaging, 2019)

Graph-Based Decoding Model for Functional Alignment of Unaligned fMRI Data. - Weida Li; Mingxia Liu 001; Fang Chen 007; Daoqiang Zhang (AAAI, 2020)

Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification. - Chunxiang Feng; Biao Jie; Xintao Ding; Daoqiang Zhang; Mingxia Liu 001 (MLMI@MICCAI, 2020)

Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network. - Hao Guan; Erkun Yang; Li Wang 026; Pew-Thian Yap; Mingxia Liu 001; Dinggang Shen (MLMI@MICCAI, 2020)

Attention-Guided Deep Domain Adaptation for Brain Dementia Identification with Multi-site Neuroimaging Data. - Hao Guan; Erkun Yang; Pew-Thian Yap; Dinggang Shen; Mingxia Liu 001 (DART/DCL@MICCAI, 2020)

Generating Dual-Energy Subtraction Soft-Tissue Images from Chest Radiographs via Bone Edge-Guided GAN. - Yunbi Liu; Mingxia Liu 001; Yuhua Xi; Genggeng Qin; Dinggang Shen; Wei Yang 006 (MICCAI (2), 2020)

Joint Neuroimage Synthesis and Representation Learning for Conversion Prediction of Subjective Cognitive Decline. - Yunbi Liu; Yongsheng Pan; Wei Yang 006; Zhenyuan Ning; Ling Yue; Mingxia Liu 001; Dinggang Shen (MICCAI (7), 2020)

LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI. - Zhenyuan Ning; Yu Zhang 064; Yongsheng Pan; Tao Zhong 002; Mingxia Liu 001; Dinggang Shen (MLMI@MICCAI, 2020)

Deep Disentangled Hashing with Momentum Triplets for Neuroimage Search. - Erkun Yang; Dongren Yao; Bing Cao 002; Hao Guan; Pew-Thian Yap; Dinggang Shen; Mingxia Liu 001 (MICCAI (1), 2020)

Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder Using Resting-State fMRI. - Dongren Yao; Jing Sui; Erkun Yang; Pew-Thian Yap; Dinggang Shen; Mingxia Liu 001 (MLMI@MICCAI, 2020)

Nyström Subspace Learning for Large-scale SVMs. - Weida Li; Mingxia Liu 001; Daoqiang Zhang (CoRR, 2020)

Synergistic Learning of Lung Lobe Segmentation and Hierarchical Multi-Instance Classification for Automated Severity Assessment of COVID-19 in CT Images. - Kelei He; Wei Zhao 040; Xingzhi Xie; Wen Ji; Mingxia Liu 001; Zhenyu Tang 002; Feng Shi 001; Yang Gao 001; Jun Liu 075; Junfeng Zhang; Dinggang Shen (CoRR, 2020)

A Survey on Deep Learning for Neuroimaging-based Brain Disorder Analysis. - Li Zhang; Mingliang Wang; Mingxia Liu 001; Daoqiang Zhang (CoRR, 2020)

Designing weighted correlation kernels in convolutional neural networks for functional connectivity based brain disease diagnosis. - Biao Jie; Mingxia Liu 001; Chunfeng Lian; Feng Shi 001; Dinggang Shen (Medical Image Anal., 2020)

Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization. - Jun Zhang 018; Mingxia Liu 001; Li Wang 026; Si Chen; Peng Yuan 001; Jianfu Li; Steve Guo-Fang Shen; Zhen Tang; Ken-Chung Chen; James J. Xia; Dinggang Shen (Medical Image Anal., 2020)

Multi-modal latent space inducing ensemble SVM classifier for early dementia diagnosis with neuroimaging data. - Tao Zhou 002; Kim-Han Thung; Mingxia Liu 001; Feng Shi 001; Changqing Zhang; Dinggang Shen (Medical Image Anal., 2020)

Hierarchical Structured Sparse Learning for Schizophrenia Identification. - Mingliang Wang; Xiaoke Hao; Jiashuang Huang; Kangcheng Wang; Li Shen 001; Xijia Xu; Daoqiang Zhang; Mingxia Liu 001 (Neuroinformatics, 2020)

Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI. - Chunfeng Lian; Mingxia Liu 001; Jun Zhang 018; Dinggang Shen (IEEE Trans. Pattern Anal. Mach. Intell., 2020)

Spatial-Temporal Dependency Modeling and Network Hub Detection for Functional MRI Analysis via Convolutional-Recurrent Network. - Mingliang Wang; Chunfeng Lian; Dongren Yao; Daoqiang Zhang; Mingxia Liu 001; Dinggang Shen (IEEE Trans. Biomed. Eng., 2020)

Querying Representative and Informative Super-Pixels for Filament Segmentation in Bioimages. - Wei Shao 005; Sheng-Jun Huang; Mingxia Liu 001; Daoqiang Zhang (IEEE ACM Trans. Comput. Biol. Bioinform., 2020)

Weakly Supervised Deep Learning for Brain Disease Prognosis Using MRI and Incomplete Clinical Scores. - Mingxia Liu 001; Jun Zhang 018; Chunfeng Lian; Dinggang Shen (IEEE Trans. Cybern., 2020)

NLH: A Blind Pixel-Level Non-Local Method for Real-World Image Denoising. - Yingkun Hou; Jun Xu 019; Mingxia Liu 001; Guanghai Liu 001; Li Liu 004; Fan Zhu 001; Ling Shao 001 (IEEE Trans. Image Process., 2020)

High-Order Feature Learning for Multi-Atlas Based Label Fusion: Application to Brain Segmentation With MRI. - Liang Sun 009; Wei Shao 005; Mingliang Wang; Daoqiang Zhang; Mingxia Liu 001 (IEEE Trans. Image Process., 2020)

Erratum to "Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting". - Zhenghan Fang; Yong Chen; Mingxia Liu 001; Lei Xiang; Qian Zhang 066; Qian Wang 001; Weili Lin; Dinggang Shen (IEEE Trans. Medical Imaging, 2020)

Spatially-Constrained Fisher Representation for Brain Disease Identification With Incomplete Multi-Modal Neuroimages. - Yongsheng Pan; Mingxia Liu 001; Chunfeng Lian; Yong Xia 001; Dinggang Shen (IEEE Trans. Medical Imaging, 2020)

Anatomical Attention Guided Deep Networks for ROI Segmentation of Brain MR Images. - Liang Sun 009; Wei Shao 005; Daoqiang Zhang; Mingxia Liu 001 (IEEE Trans. Medical Imaging, 2020)

Identifying Autism Spectrum Disorder With Multi-Site fMRI via Low-Rank Domain Adaptation. - Mingliang Wang; Daoqiang Zhang; Jiashuang Huang; Pew-Thian Yap; Dinggang Shen; Mingxia Liu 001 (IEEE Trans. Medical Imaging, 2020)

Multi-Source Domain Adaptation via Optimal Transport for Brain Dementia Identification. - Hao Guan; Li Wang 026; Mingxia Liu 001 (ISBI, 2021)

Deep Factor Regression For Computer-Aided Analysis of Major Depressive Disorders With Structural MRI Data. - Erkun Yang; Lihong Wang; David C. Steffens; Guy G. Potter; Mingxia Liu 001 (ISBI, 2021)

Integration of Handcrafted and Embedded Features from Functional Connectivity Network with rs-fMRI forBrain Disease Classification. - Peng Dong; Biao Jie; Lin Kai; Xintao Ding; Weixin Bian; Mingxia Liu 001 (MLMI@MICCAI, 2021)

Cost-Sensitive Meta-learning for Progress Prediction of Subjective Cognitive Decline with Brain Structural MRI. - Hao Guan; Yunbi Liu; Shifu Xiao; Ling Yue; Mingxia Liu 001 (MICCAI (5), 2021)

Learning Transferable 3D-CNN for MRI-Based Brain Disorder Classification from Scratch: An Empirical Study. - Hao Guan; Li Wang 026; Dongren Yao; Andrea Bozoki; Mingxia Liu 001 (MLMI@MICCAI, 2021)

Extracting Sequential Features from Dynamic Connectivity Network with rs-fMRI Data for AD Classification. - Kai Lin; Biao Jie; Peng Dong; Xintao Ding; Weixin Bian; Mingxia Liu 001 (MLMI@MICCAI, 2021)

Improving Tuberculosis Recognition on Bone-Suppressed Chest X-Rays Guided by Task-Specific Features. - Yunbi Liu; Genggeng Qin; Yun Liu; Mingxia Liu 001; Wei Yang 006 (PRIME@MICCAI, 2021)

Tensor-Based Multi-index Representation Learning for Major Depression Disorder Detection with Resting-State fMRI. - Dongren Yao; Erkun Yang; Hao Guan; Jing Sui; Zhizhong Zhang; Mingxia Liu 001 (MICCAI (5), 2021)

Integrating Multimodal MRIs for Adult ADHD Identification with Heterogeneous Graph Attention Convolutional Network. - Dongren Yao; Erkun Yang; Li Sun; Jing Sui; Mingxia Liu 001 (PRIME@MICCAI, 2021)

Estimating sparse functional connectivity networks via hyperparameter-free learning model. - Lei Sun; Yanfang Xue; Yining Zhang; Lishan Qiao; Limei Zhang; Mingxia Liu 001 (Artif. Intell. Medicine, 2021)

Multi-Scale Graph Representation Learning for Autism Identification With Functional MRI. - Ying Chu; Guangyu Wang; Liang Cao; Lishan Qiao; Mingxia Liu 001 (Frontiers Neuroinformatics, 2021)

Multi-site MRI harmonization via attention-guided deep domain adaptation for brain disorder identification. - Hao Guan; Yunbi Liu; Erkun Yang; Pew-Thian Yap; Dinggang Shen; Mingxia Liu 001 (Medical Image Anal., 2021)

Modeling dynamic characteristics of brain functional connectivity networks using resting-state functional MRI. - Mingliang Wang; Jiashuang Huang; Mingxia Liu 001; Daoqiang Zhang (Medical Image Anal., 2021)

Towards evaluating the robustness of deep diagnostic models by adversarial attack. - Mengting Xu; Tao Zhang 099; Zhongnian Li; Mingxia Liu 001; Daoqiang Zhang (Medical Image Anal., 2021)

Joint fully convolutional and graph convolutional networks for weakly-supervised segmentation of pathology images. - Jun Zhang 018; Zhiyuan Hua; Kezhou Yan; Kuan Tian; Jianhua Yao 001; Eryun Liu; Mingxia Liu 001; Xiao Han 011 (Medical Image Anal., 2021)

Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images. - Kelei He; Wei Zhao 040; Xingzhi Xie; Wen Ji; Mingxia Liu 001; Zhenyu Tang 002; Yinghuan Shi; Feng Shi 001; Yang Gao 001; Jun Liu 075; Junfeng Zhang; Dinggang Shen (Pattern Recognit., 2021)

Group-Wise Learning for Aurora Image Classification With Multiple Representations. - Jun Zhang 018; Mingxia Liu 001; Ke Lu 002; Yue Gao 002 (IEEE Trans. Cybern., 2021)

Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract. - Shuai Wang 003; Yang Cong; Hancan Zhu; Xianyi Chen; Liangqiong Qu; Huijie Fan; Qiang Zhang 008; Mingxia Liu 001 (IEEE J. Biomed. Health Informatics, 2021)

Boundary Coding Representation for Organ Segmentation in Prostate Cancer Radiotherapy. - Shuai Wang 003; Mingxia Liu 001; Jun Lian; Dinggang Shen (IEEE Trans. Medical Imaging, 2021)

Deep Bayesian Hashing With Center Prior for Multi-Modal Neuroimage Retrieval. - Erkun Yang; Mingxia Liu 001; Dongren Yao; Bing Cao 002; Chunfeng Lian; Pew-Thian Yap; Dinggang Shen (IEEE Trans. Medical Imaging, 2021)

A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity. - Dongren Yao; Jing Sui; Mingliang Wang; Erkun Yang; Yeerfan Jiaerken; Na Luo; Pew-Thian Yap; Mingxia Liu 001; Dinggang Shen (IEEE Trans. Medical Imaging, 2021)

Prediction of HPV-Associated Genetic Diversity for Squamous Cell Carcinoma of Head and Neck Cancer Based on 18F-FDG PET/CT. - Yuqi Fang; Jorge Daniel Oldan; Weili Lin; Travis Parke Schrank; Wendell Gray Yarbrough; Natalia Isaeva; Mingxia Liu 001 (MLMI@MICCAI, 2022)

Fast Image-Level MRI Harmonization via Spectrum Analysis. - Hao Guan; Siyuan Liu 004; Weili Lin; Pew-Thian Yap; Mingxia Liu 001 (MLMI@MICCAI, 2022)

Function MRI Representation Learning via Self-supervised Transformer for Automated Brain Disorder Analysis. - Qianqian Wang 004; Lishan Qiao; Mingxia Liu 001 (MLMI@MICCAI, 2022)

Domain-Prior-Induced Structural MRI Adaptation for Clinical Progression Prediction of Subjective Cognitive Decline. - Minhui Yu; Hao Guan; Yuqi Fang; Ling Yue; Mingxia Liu 001 (MICCAI (1), 2022)

Understanding Clinical Progression of Late-Life Depression to Alzheimer's Disease Over 5 Years with Structural MRI. - Lintao Zhang; Minhui Yu; Lihong Wang; David C. Steffens; Rong Wu; Guy G. Potter; Mingxia Liu 001 (MLMI@MICCAI, 2022)

Bootstrapping Joint Entity and Relation Extraction with Reinforcement Learning. - Ming-Xia Liu 001; Xiang Cheng 003; Sen Su; Ming Kuang; Gang Li 001 (WISE, 2022)

Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI. - Hao Guan; Ling Yue; Pew-Thian Yap; Andrea Bozoki; Mingxia Liu 001 (CoRR, 2022)

Adaptive Multimodal Neuroimage Integration for Major Depression Disorder Detection. - Qianqian Wang 004; Long Li; Lishan Qiao; Mingxia Liu 001 (Frontiers Neuroinformatics, 2022)

Editorial: Weakly supervised deep learning-based methods for brain image analysis. - Hancan Zhu; Mingxia Liu 001; Zhenyu Tang 002; Shuai Wang 003 (Frontiers Neuroinformatics, 2022)

Efficient Partitioning Method for Optimizing the Compression on Array Data. - Shuai Han; Mingxia Liu 001; Jian-Zhong Li (J. Comput. Sci. Technol., 2022)

Estimating high-order brain functional networks by correlation-preserving embedding. - Hui Su; Limei Zhang; Lishan Qiao; Mingxia Liu 001 (Medical Biol. Eng. Comput., 2022)

Assessing clinical progression from subjective cognitive decline to mild cognitive impairment with incomplete multi-modal neuroimages. - Yunbi Liu; Ling Yue; Shifu Xiao; Wei Yang 006; Dinggang Shen; Mingxia Liu 001 (Medical Image Anal., 2022)

Multi-site clustering and nested feature extraction for identifying autism spectrum disorder with resting-state fMRI. - Nan Wang; Dongren Yao; Lizhuang Ma; Mingxia Liu 001 (Medical Image Anal., 2022)

Consistent connectome landscape mining for cross-site brain disease identification using functional MRI. - Mingliang Wang; Daoqiang Zhang; Jiashuang Huang; Mingxia Liu 001; Qingshan Liu (Medical Image Anal., 2022)

Disease-Image-Specific Learning for Diagnosis-Oriented Neuroimage Synthesis With Incomplete Multi-Modality Data. - Yongsheng Pan; Ming-Xia Liu 001; Yong Xia 001; Dinggang Shen (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Domain Adaptation for Medical Image Analysis: A Survey. - Hao Guan; Mingxia Liu 001 (IEEE Trans. Biomed. Eng., 2022)

Multiview Feature Learning With Multiatlas-Based Functional Connectivity Networks for MCI Diagnosis. - Yu Zhang 009; Han Zhang 002; Ehsan Adeli 001; Xiaobo Chen 001; Mingxia Liu 001; Dinggang Shen (IEEE Trans. Cybern., 2022)

Attention-Guided Hybrid Network for Dementia Diagnosis With Structural MR Images. - Chunfeng Lian; Mingxia Liu 001; Yongsheng Pan; Dinggang Shen (IEEE Trans. Cybern., 2022)

Distribution-Guided Network Thresholding for Functional Connectivity Analysis in fMRI-Based Brain Disorder Identification. - Zhengdong Wang; Biao Jie; Chunxiang Feng; Taochun Wang; Weixin Bian; Xintao Ding; Wen Zhou 005; Mingxia Liu 001 (IEEE J. Biomed. Health Informatics, 2022)

Multi-Task Weakly-Supervised Attention Network for Dementia Status Estimation With Structural MRI. - Chunfeng Lian; Mingxia Liu 001; Li Wang 026; Dinggang Shen (IEEE Trans. Neural Networks Learn. Syst., 2022)

Modularity-Constrained Dynamic Representation Learning for Interpretable Brain Disorder Analysis with Functional MRI. - Qianqian Wang 004; Mengqi Wu; Yuqi Fang; Wei Wang 411; Lishan Qiao; Ming-Xia Liu 001 (MICCAI (1), 2023)

Hybrid Multimodality Fusion with Cross-Domain Knowledge Transfer to Forecast Progression Trajectories in Cognitive Decline. - Minhui Yu; Yunbi Liu; Jinjian Wu; Andrea Bozoki; Shijun Qiu; Ling Yue; Mingxia Liu 001 (MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI, 2023)

Brain Anatomy-Guided MRI Analysis for Assessing Clinical Progression of Cognitive Impairment with Structural MRI. - Lintao Zhang; Jinjian Wu; Lihong Wang; Li Wang 026; David C. Steffens; Shijun Qiu; Guy G. Potter; Mingxia Liu 001 (MICCAI (8), 2023)

Triplet Learning for Chest X-Ray Image Search in Automated COVID-19 Analysis. - Linmin Wang; Qianqian Wang 004; Xiaochuan Wang; Yunling Ma; Lishan Qiao; Mingxia Liu 001 (MLMI@MICCAI (2), 2023)

Structural MRI Harmonization via Disentangled Latent Energy-Based Style Translation. - Mengqi Wu; Lintao Zhang; Pew-Thian Yap; Weili Lin; Hongtu Zhu; Mingxia Liu 001 (MLMI@MICCAI (1), 2023)

Deep Bayesian Quantization for Supervised Neuroimage Search. - Erkun Yang; Cheng Deng; Mingxia Liu 001 (MLMI@MICCAI (2), 2023)

Specificity-Aware Federated Graph Learning for Brain Disorder Analysis with Functional MRI. - Junhao Zhang; Xiaochuan Wang; Qianqian Wang 004; Lishan Qiao; Mingxia Liu 001 (MLMI@MICCAI (2), 2023)

Federated Learning for Medical Image Analysis: A Survey. - Hao Guan; Mingxia Liu 001 (CoRR, 2023)

Source-Free Collaborative Domain Adaptation via Multi-Perspective Feature Enrichment for Functional MRI Analysis. - Yuqi Fang; Jinjian Wu; Qianqian Wang 004; Shijun Qiu; Andrea Bozoki; Huaicheng Yan 001; Mingxia Liu 001 (CoRR, 2023)

Unsupervised cross-domain functional MRI adaptation for automated major depressive disorder identification. - Yuqi Fang; Mingliang Wang; Guy G. Potter; Mingxia Liu 001 (Medical Image Anal., 2023)

DomainATM: Domain adaptation toolbox for medical data analysis. - Hao Guan; Mingxia Liu 001 (NeuroImage, 2023)

Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline With Structural MRI. - Hao Guan; Ling Yue; Pew-Thian Yap; Shifu Xiao; Andrea Bozoki; Mingxia Liu 001 (IEEE J. Biomed. Health Informatics, 2023)

Attention-Enhanced Fusion of Structural and Functional MRI for Analyzing HIV-Associated Asymptomatic Neurocognitive Impairment. - Yuqi Fang; Wei Wang 411; Qianqian Wang 004; Hong-Jun Li; Mingxia Liu 001 (MICCAI (11), 2024)

Iterative Learning for Joint Image Denoising and Motion Artifact Correction of 3D Brain MRI. - Lintao Zhang; Mengqi Wu; Lihong Wang; David C. Steffens; Guy G. Potter; Mingxia Liu 001 (CoRR, 2024)

Functional Imaging Constrained Diffusion for Brain PET Synthesis from Structural MRI. - Minhui Yu; Mengqi Wu; Ling Yue; Andrea Bozoki; Mingxia Liu 001 (CoRR, 2024)

Augmentation-based Unsupervised Cross-Domain Functional MRI Adaptation for Major Depressive Disorder Identification. - Yunling Ma; Chaojun Zhang; Xiaochuan Wang; Qianqian Wang 004; Liang Cao; Limei Zhang; Mingxia Liu 001 (CoRR, 2024)

Unpaired Volumetric Harmonization of Brain MRI with Conditional Latent Diffusion. - Mengqi Wu; Minhui Yu; Shuaiming Jing; Pew-Thian Yap; Zhengwu Zhang; Mingxia Liu 001 (CoRR, 2024)

Hybrid representation learning for cognitive diagnosis in late-life depression over 5 years with structural MRI. - Lintao Zhang; Lihong Wang; Minhui Yu; Rong Wu; David C. Steffens; Guy G. Potter; Mingxia Liu 001 (Medical Image Anal., 2024)

Source-free unsupervised domain adaptation: A survey. - Yuqi Fang; Pew-Thian Yap; Weili Lin; Hongtu Zhu; Ming-Xia Liu 001 (Neural Networks, 2024)

Triplet-constrained deep hashing for chest X-ray image retrieval in COVID-19 assessment. - Linmin Wang; Qianqian Wang 004; Xiaochuan Wang; Yunling Ma; Limei Zhang; Mingxia Liu 001 (Neural Networks, 2024)

Learning functional brain networks with heterogeneous connectivities for brain disease identification. - Chaojun Zhang; Yunling Ma; Lishan Qiao; Limei Zhang; Mingxia Liu 001 (Neural Networks, 2024)

Federated learning for medical image analysis: A survey. - Hao Guan; Pew-Thian Yap; Andrea Bozoki; Mingxia Liu 001 (Pattern Recognit., 2024)

Graph Convolutional Network With Self-Supervised Learning for Brain Disease Classification. - Guangyu Wang; Ying Chu; Qianqian Wang 004; Limei Zhang; Lishan Qiao; Mingxia Liu 001 (IEEE ACM Trans. Comput. Biol. Bioinform., 2024)

Preserving specificity in federated graph learning for fMRI-based neurological disorder identification. - Junhao Zhang; Qianqian Wang 004; Xiaochuan Wang; Lishan Qiao; Mingxia Liu 001 (Neural Networks, 2024)

Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI. - Qianqian Wang 004; Wei Wang 411; Yuqi Fang; Pew-Thian Yap; Hongtu Zhu; Hong-Jun Li; Lishan Qiao; Mingxia Liu 001 (IEEE Trans. Biomed. Eng., 2024)

Topology-Aware Graph Augmentation for Predicting Clinical Trajectories in Neurocognitive Disorders. - Qianqian Wang 004; Wei Wang 411; Yuqi Fang; Hong-Jun Li; Andrea Bozoki; Mingxia Liu 001 (ISBI, 2025)

AEPL: Automated and Editable Prompt Learning for Brain Tumor Segmentation. - Yongheng Sun; Mingxia Liu 001; Chunfeng Lian (ISBI, 2025)

R2Gen-Mamba: A Selective State Space Model for Radiology Report Generation. - Yongheng Sun; Yueh Z. Lee; Genevieve A. Woodard; Hongtu Zhu; Chunfeng Lian; Mingxia Liu 001 (ISBI, 2025)

Self-supervised graph contrastive learning with diffusion augmentation for functional MRI analysis and brain disorder detection. - Xiaochuan Wang; Yuqi Fang; Qianqian Wang 004; Pew-Thian Yap; Hongtu Zhu; Mingxia Liu 001 (Medical Image Anal., 2025)

ACTION: Augmentation and computation toolbox for brain network analysis with functional MRI. - Yuqi Fang; Junhao Zhang; Linmin Wang; Qianqian Wang 004; Mingxia Liu 001 (NeuroImage, 2025)

Dynamic domain generalization for medical image segmentation. - Zhiming Cheng; Mingxia Liu 001; Chenggang Yan 001; Shuai Wang 003 (Neural Networks, 2025)

Riemannian manifold-based disentangled representation learning for multi-site functional connectivity analysis. - Wenyang Li; Mingliang Wang; Mingxia Liu 001; Qingshan Liu (Neural Networks, 2025)

Disentangled latent energy-based style translation: An image-level structural MRI harmonization framework. - Mengqi Wu; Lintao Zhang; Pew-Thian Yap; Hongtu Zhu; Mingxia Liu 001 (Neural Networks, 2025)

Hybrid multi-modality multi-task learning for forecasting progression trajectories in subjective cognitive decline. - Minhui Yu; Yuqi Fang; Yunbi Liu; Andrea C. Bozoki; Shifu Xiao; Ling Yue; Mingxia Liu 001 (Neural Networks, 2025)

Domain generalization for image classification with dynamic decision boundary. - Zhiming Cheng; Mingxia Liu 001; Defu Yang; Zhidong Zhao; Chenggang Yan 001; Shuai Wang 003 (Pattern Recognit., 2025)

Source-free collaborative domain adaptation via multi-perspective feature enrichment for functional MRI analysis. - Yuqi Fang; Jinjian Wu; Qianqian Wang 004; Shijun Qiu; Andrea Bozoki; Mingxia Liu 001 (Pattern Recognit., 2025)

Graph augmentation guided federated knowledge distillation for multisite functional MRI analysis. - Qianqian Wang 004; Junhao Zhang; Long Li; Lishan Qiao; Pew-Thian Yap; Mingxia Liu 001 (Pattern Recognit., 2025)

Brain anatomy prior modeling to forecast clinical progression of cognitive impairment with structural MRI. - Lintao Zhang; Jinjian Wu; Lihong Wang; Li Wang 026; David C. Steffens; Shijun Qiu; Guy G. Potter; Mingxia Liu 001 (Pattern Recognit., 2025)

DCLNet: Double Collaborative Learning Network on Stationary-Dynamic Functional Brain Network for Brain Disease Classification. - Jie Zhou; Biao Jie; Zhengdong Wang; Zhixiang Zhang; Weixin Bian; Yang Yang 140; Hongwei Li; Fengyun Sun; Mingxia Liu 001 (IEEE Trans. Image Process., 2025)

Hyperbolic Kernel Graph Neural Networks for Neurocognitive Decline Analysis from Multimodal Brain Imaging. - Meimei Yang; Yongheng Sun; Qianqian Wang 004; Andrea Bozoki; Maureen Kohi; Mingxia Liu 001 (CoRR, 2025)

Learning from Heterogeneous Structural MRI via Collaborative Domain Adaptation for Late-Life Depression Assessment. - Yuzhen Gao; Qianqian Wang 004; Yongheng Sun; Cui Wang; Yongquan Liang; Mingxia Liu 001 (CoRR, 2025)