Mingxia Liu

发表

Label-aligned multi-task feature learning for multimodal classification of Alzheimer’s disease and mild cognitive impairment

Daoqiang Zhang, Songcan Chen, D. Shen, 2015, Brain Imaging and Behavior.

Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images

Dinggang Shen, Wen Ji, Feng Shi, 2020, Pattern Recognition.

Constructing High-Order Dynamic Functional Connectivity Networks from Resting-State fMRI for Brain Dementia Identification

Daoqiang Zhang, Biao Jie, Mingxia Liu, 2020, MLMI@MICCAI.

Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI

P. Yap, Mingxia Liu, A. Bozoki, 2022, 2206.12480.

Assessing clinical progression from subjective cognitive decline to mild cognitive impairment with incomplete multi-modal neuroimages

Dinggang Shen, Yunbi Liu, Ling Yue, 2021, Medical Image Anal..

Brain-Wide Genome-Wide Association Study for Alzheimer's Disease via Joint Projection Learning and Sparse Regression Model

Dinggang Shen, Kim-Han Thung, Mingxia Liu, 2019, IEEE Transactions on Biomedical Engineering.

Convolutional Recurrent Neural Network for Dynamic Functional MRI Analysis and Brain Disease Identification

Biao Jie, Mingxia Liu, Xintao Ding, 2022, Frontiers in Neuroscience.

Erratum: Deep Learning for Fast and Spatially Constrained Tissue Quantification from Highly Accelerated Data in Magnetic Resonance Fingerprinting (IEEE Transactions on Medical Imaging (2019) 38:10 (2364-2374) DOI: 10.1109/tmi.2019.2899328)

Qian Wang, Dinggang Shen, Qian Zhang, 2020 .

Associations of lifetime concussion history and repetitive head impact exposure with resting-state functional connectivity in former collegiate American football players: An NCAA 15-year follow-up study

K. Guskiewicz, Mingxia Liu, M. McCrea, 2022, PloS one.

Resting-State Functional MRI Adaptation with Attention Graph Convolution Network for Brain Disorder Identification

Lishan Qiao, Mingxia Liu, Ying Chu, 2022, Brain sciences.

Resting-State Functional MRI Adaptation with Attention Graph Convolution Network for Brain Disorder Identification

Lishan Qiao, Mingxia Liu, Ying Chu, 2022, Brain sciences.

Deep Hash with Optimal Transport-Based Domain Adaptation for Multisite MRI Retrieval

Mingxia Liu, Jingcheng Yang, Sijie Niu, 2022, Wireless Communications and Mobile Computing.

Hybrid Representation Learning for Cognitive Diagnosis in Late-Life Depression Over 5 Years with Structural MRI

Lihong Wang, D. Steffens, G. Potter, 2022, Medical Image Anal..

Unsupervised cross-domain functional MRI adaptation for automated major depressive disorder identification

Yuqi Fang, G. Potter, Mingxia Liu, 2023, Medical Image Anal..

Modularity-Guided Functional Brain Network Analysis for Early-Stage Dementia Identification

Lishan Qiao, Mingxia Liu, Xiao Jiang, 2021, Frontiers in Neuroscience.

A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis

Mingliang Wang, Li Zhang, Mingxia Liu, 2020, Frontiers in Neuroscience.

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis

Dinggang Shen, Jun Zhang, Ehsan Adeli, 2019, IEEE Transactions on Biomedical Engineering.

Tensor-Based Multi-index Representation Learning for Major Depression Disorder Detection with Resting-State fMRI

Jing Sui, Dongren Yao, Hao Guan, 2021, MICCAI.

First-year development of modules and hubs in infant brain functional networks

Dinggang Shen, Jun Zhang, Han Zhang, 2019, NeuroImage.

An Organelle Correlation-Guided Feature Selection Approach for Classifying Multi-Label Subcellular Bio-Images

Daoqiang Zhang, Hong-Bin Shen, Mingxia Liu, 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Integrating Multimodal MRIs for Adult ADHD Identification with Heterogeneous Graph Attention Convolutional Network

Dongren Yao, Mingxia Liu, Erkun Yang, 2021, PRIME@MICCAI.

Multi-site clustering and nested feature extraction for identifying autism spectrum disorder with resting-state fMRI

Lizhuang Ma, Dongren Yao, Nan Wang, 2021, Medical Image Anal..

Designing weighted correlation kernels in convolutional neural networks for functional connectivity based brain disease diagnosis

Chunfeng Lian, Biao Jie, Feng Shi, 2020, Medical Image Anal..

Joint fully convolutional and graph convolutional networks for weakly-supervised segmentation of pathology images

Eryun Liu, Kuan Tian, Zhiyuan Hua, 2021, Medical Image Anal..

Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings

Yinghuan Shi, Heung-Il Suk, Mingxia Liu, 2018, MLMI@MICCAI.

Temporal-Adaptive Graph Convolutional Network for Automated Identification of Major Depressive Disorder Using Resting-State fMRI

Dinggang Shen, Erkun Yang, Mingxia Liu, 2020, MLMI@MICCAI.

Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI

Dinggang Shen, Jun Zhang, Chunfeng Lian, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline With Structural MRI

P. Yap, Mingxia Liu, A. Bozoki, 2022, IEEE Journal of Biomedical and Health Informatics.

Fast Image-Level MRI Harmonization via Spectrum Analysis

Weili Lin, P. Yap, Mingxia Liu, 2022, MLMI@MICCAI.

Detecting type 2 diabetes mellitus cognitive impairment using whole-brain functional connectivity

P. Yap, Yuqi Fang, S. Qiu, 2023, Scientific Reports.

Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack

Tao Zhang, Mengting Xu, Daoqiang Zhang, 2021, Medical Image Anal..

Anatomical-Landmark-Based Deep Learning for Alzheimer’s Disease Diagnosis with Structural Magnetic Resonance Imaging

Chunfeng Lian, Dinggang Shen, Mingxia Liu, 2019 .

Multi-Task Weakly-Supervised Attention Network for Dementia Status Estimation With Structural MRI

D. Shen, Li Wang, C. Lian, 2021, IEEE Transactions on Neural Networks and Learning Systems.

Spatially-Constrained Fisher Representation for Brain Disease Identification With Incomplete Multi-Modal Neuroimages

Chunfeng Lian, Yong Xia, Dinggang Shen, 2020, IEEE Transactions on Medical Imaging.

Joint Neuroimage Synthesis and Representation Learning for Conversion Prediction of Subjective Cognitive Decline

Dinggang Shen, Mingxia Liu, Wei Yang, 2020, MICCAI.

Multi-Scale Context-Guided Deep Network for Automated Lesion Segmentation With Endoscopy Images of Gastrointestinal Tract

Shuai Wang, Huijie Fan, Hancan Zhu, 2020, IEEE Journal of Biomedical and Health Informatics.

Domain-Prior-Induced Structural MRI Adaptation for Clinical Progression Prediction of Subjective Cognitive Decline

Yuqi Fang, Mingxia Liu, Minhui Yu, 2022, MICCAI.

Deep Disentangled Hashing with Momentum Triplets for Neuroimage Search

Dinggang Shen, Erkun Yang, Mingxia Liu, 2020, MICCAI.

Graph Learning in Medical Imaging: First International Workshop, GLMI 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings

Zhengdong Wang, Biao Jie, Wen Zhou, 2019, GLMI@MICCAI.

NLH: A Blind Pixel-Level Non-Local Method for Real-World Image Denoising

Ling Shao, Jun Xu, Yingkun Hou, 2019, IEEE Transactions on Image Processing.

Integration of Handcrafted and Embedded Features from Functional Connectivity Network with rs-fMRI forBrain Disease Classification

Biao Jie, Weixin Bian, Mingxia Liu, 2021, MLMI@MICCAI.

Adaptive Thresholding of Functional Connectivity Networks for fMRI-Based Brain Disease Analysis

Zhengdong Wang, Biao Jie, Dinggang Shen, 2019, GLMI@MICCAI.

Attention-Guided Deep Domain Adaptation for Brain Dementia Identification with Multi-site Neuroimaging Data

Dinggang Shen, Erkun Yang, Pew-Thian Yap, 2020, DART/DCL@MICCAI.

Spatial-Temporal Dependency Modeling and Network Hub Detection for Functional MRI Analysis via Convolutional-Recurrent Network

Daoqiang Zhang, Mingliang Wang, Chunfeng Lian, 2019, IEEE Transactions on Biomedical Engineering.

Estimating sparse functional connectivity networks via hyperparameter-free learning model

Lishan Qiao, Limei Zhang, Yanfang Xue, 2021, Artif. Intell. Medicine.

Triplet Graph Convolutional Network for Multi-scale Analysis of Functional Connectivity Using Functional MRI

Jie Wei, Mingliang Wang, Chunfeng Lian, 2019, GLMI@MICCAI.

Robust multi-label transfer feature learning for early diagnosis of Alzheimer’s disease

Alzheimer's Disease Neuroimaging Initiative, Daoqiang Zhang, D. Shen, 2019, Brain Imaging and Behavior.

Addressing multi‐site functional MRI heterogeneity through dual‐expert collaborative learning for brain disease identification

Hongtu Zhu, Yuqi Fang, G. Potter, 2023, Human brain mapping.

High-Order Feature Learning for Multi-Atlas Based Label Fusion: Application to Brain Segmentation With MRI

Daoqiang Zhang, Liang Sun, Mingliang Wang, 2019, IEEE Transactions on Image Processing.

Reliability-based robust multi-atlas label fusion for brain MRI segmentation

Daoqiang Zhang, Wei Shao, Liang Sun, 2019, Artif. Intell. Medicine.

LDGAN: Longitudinal-Diagnostic Generative Adversarial Network for Disease Progression Prediction with Missing Structural MRI

Tao Zhong, Dinggang Shen, Mingxia Liu, 2020, MLMI@MICCAI.

A Hierarchical Feature and Sample Selection Framework and Its Application for Alzheimer’s Disease Diagnosis

Ehsan Adeli, Seong-Whan Lee, Jun Zhang, 2017, Scientific Reports.

Accurate module induced brain network construction for mild cognitive impairment identification with functional MRI

Limei Zhang, Mingxia Liu, Xiaoming Xi, 2023, Frontiers in Aging Neuroscience.

Context-guided fully convolutional networks for joint craniomaxillofacial bone segmentation and landmark digitization

Peng Yuan, Zhen Tang, Dinggang Shen, 2019, Medical Image Anal..

Machine Learning for Craniomaxillofacial Landmark Digitization of 3D Imaging

Dinggang Shen, Chunfeng Lian, Li Wang, 2021, Machine Learning in Dentistry.

Multi-modal latent space inducing ensemble SVM classifier for early dementia diagnosis with neuroimaging data

Feng Shi, Dinggang Shen, Mingxia Liu, 2019, Medical Image Anal..

Estimating high-order brain functional networks by correlation-preserving embedding

Hui Su, Limei Zhang, Lishan Qiao, 2022, Medical & Biological Engineering & Computing.

Adaptive Multimodal Neuroimage Integration for Major Depression Disorder Detection

Longhai Li, Lishan Qiao, Mingxia Liu, 2022, Frontiers in Neuroinformatics.

Brain Anatomy Prior Modeling to Forecast Clinical Progression of Cognitive Impairment with Structural MRI

Lihong Wang, D. Steffens, G. Potter, 2023, ArXiv.

Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI

P. Yap, Yuqi Fang, Lishan Qiao, 2023, IEEE Transactions on Biomedical Engineering.

Multi-Scale Graph Representation Learning for Autism Identification With Functional MRI

Lishan Qiao, Mingxia Liu, Ying Chu, 2022, Frontiers in Neuroinformatics.

Editorial: Functional and structural brain network construction, representation and application

Zhengxia Wang, Mingxia Liu, Cen Chen, 2023, Frontiers in Neuroscience.

Discriminative-Region-Aware Residual Network for Adolescent Brain Structure and Cognitive Development Analysis

Yong Xia, Dinggang Shen, Mingxia Liu, 2019, GLMI@MICCAI.

Linking Adolescent Brain MRI to Obesity via Deep Multi-cue Regression Network

Dinggang Shen, Erkun Yang, Mingxia Liu, 2020, MLMI@MICCAI.

Fusing Multiview Functional Brain Networks by Joint Embedding for Brain Disease Identification

Limei Zhang, Lishan Qiao, Mingxia Liu, 2023, Journal of personalized medicine.

Learning to Fuse Multiple Brain Functional Networks for Automated Autism Identification

Limei Zhang, Lishan Qiao, Mingxia Liu, 2023, Biology.

Future Trends of PET/MR and Utility of AI in Multi-Modal Imaging

D. Shen, P. Yap, Mingxia Liu, 2021, Hybrid PET/MR Neuroimaging.

Learning Transferable 3D-CNN for MRI-Based Brain Disorder Classification from Scratch: An Empirical Study

Dongren Yao, Hao Guan, Li Wang, 2021, MLMI@MICCAI.

Functional Connectivity Network Analysis with Discriminative Hub Detection for Brain Disease Identification

Daoqiang Zhang, Mingliang Wang, Mingxia Liu, 2019, AAAI.

Extracting Sequential Features from Dynamic Connectivity Network with rs-fMRI Data for AD Classification

Biao Jie, Weixin Bian, Mingxia Liu, 2021, MLMI@MICCAI.

Preserving Specificity in Federated Graph Learning for fMRI-based Neurological Disorder Identification

Junhao Zhang, Lishan Qiao, Mingxia Liu, 2023, Neural networks : the official journal of the International Neural Network Society.

Cost-Sensitive Meta-learning for Progress Prediction of Subjective Cognitive Decline with Brain Structural MRI

Yunbi Liu, Hao Guan, Ling Yue, 2021, MICCAI.

Deep Factor Regression For Computer-Aided Analysis of Major Depressive Disorders With Structural MRI Data

Erkun Yang, David C. Steffens, Guy G. Potter, 2021, 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI).

Multi-Task Weakly-Supervised Attention Network for Dementia Prediction with Structural MRI

D. Shen, Li Wang, C. Lian, 2019 .

Source-Free Collaborative Domain Adaptation via Multi-Perspective Feature Enrichment for Functional MRI Analysis

S. Qiu, Mingxia Liu, A. Bozoki, 2023, ArXiv.

Brain morphometric features predict depression symptom phenotypes in late-life depression using a deep learning model

Han Zhang, Lihong Wang, D. Steffens, 2023, Frontiers in neuroscience.

Hierarchical Fully Convolutional Network for Joint Atrophy Localization and Alzheimer's Disease Diagnosis Using Structural MRI

D. Shen, C. Lian, Mingxia Liu, 2020, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings

Heung-Il Suk, Mingxia Liu, Yinghuan Shi, 2018, MLMI@MICCAI.

Graph-Based Decoding Model for Functional Alignment of Unaligned fMRI Data

Daoqiang Zhang, Mingxia Liu, Fang Chen, 2019, AAAI Conference on Artificial Intelligence.

Estimating high-order brain functional network via signed random walk for mild cognitive impairment identification

Hui Su, Mingxia Liu, Ting-Ting Guo, 2022, Brain Network and Modulation.

Self-supervised learning with application for infant cerebellum segmentation and analysis

Gang Li, Mingxia Liu, W. Lin, 2023, Nature communications.

Multi-Scale Dynamic Graph Learning for Brain Disorder Detection With Functional MRI

Longhai Li, Lishan Qiao, Mingxia Liu, 2023, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Accurate module induced brain network construction for mild cognitive impairment identification with functional MRI

Limei Zhang, Mingxia Liu, Xiaoming Xi, 2023, Frontiers in Aging Neuroscience.