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ORCIDMingxia Liu 0001
Ming-Xia Liu 0001
Person information
- affiliation: University of North Carolina, Department of Radiology and BRIC, Chapel Hill, NC, USA
- affiliation: Taishan University, School of Information Science and Technology, Tai'an, China
- affiliation (PhD 2015): Nanjing University of Aeronautics and Astronautics, School of Computer Science and Technology, Nanjing, China
Other persons with the same name
- Mingxia Liu 0002 — Shanghai University of Engineering Science, College of Electronic and Electrical Engineering, Shanghai, China
- Mingxia Liu 0003 — Southeast University, National Mobile Communications Research Laboratory, Nanjing, China
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2020 – today
- 2023
[j81]Yuqi Fang
, Mingliang Wang, Guy G. Potter, Mingxia Liu:
Unsupervised cross-domain functional MRI adaptation for automated major depressive disorder identification. Medical Image Anal. 84: 102707 (2023)- [j80]Hao Guan, Mingxia Liu:
DomainATM: Domain adaptation toolbox for medical data analysis. NeuroImage 268: 119863 (2023) - [j79]Hao Guan, Ling Yue, Pew-Thian Yap, Shifu Xiao, Andrea Bozoki, Mingxia Liu:
Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline With Structural MRI. IEEE J. Biomed. Health Informatics 27(6): 2980-2989 (2023) - [c66]Qianqian Wang, Mengqi Wu, Yuqi Fang, Wei Wang, Lishan Qiao, Ming-Xia Liu:
Modularity-Constrained Dynamic Representation Learning for Interpretable Brain Disorder Analysis with Functional MRI. MICCAI (1) 2023: 46-56 - [c65]Lintao Zhang, Jinjian Wu, Lihong Wang, Li Wang, David C. Steffens, Shijun Qiu, Guy G. Potter, Mingxia Liu:
Brain Anatomy-Guided MRI Analysis for Assessing Clinical Progression of Cognitive Impairment with Structural MRI. MICCAI (8) 2023: 109-119 - [c64]Mengqi Wu, Lintao Zhang, Pew-Thian Yap, Weili Lin, Hongtu Zhu, Mingxia Liu:
Structural MRI Harmonization via Disentangled Latent Energy-Based Style Translation. MLMI@MICCAI (1) 2023: 1-11 - [c63]Junhao Zhang, Xiaochuan Wang, Qianqian Wang, Lishan Qiao, Mingxia Liu:
Specificity-Aware Federated Graph Learning for Brain Disorder Analysis with Functional MRI. MLMI@MICCAI (2) 2023: 43-52 - [c62]Erkun Yang, Cheng Deng, Mingxia Liu:
Deep Bayesian Quantization for Supervised Neuroimage Search. MLMI@MICCAI (2) 2023: 396-406 - [c61]Linmin Wang, Qianqian Wang, Xiaochuan Wang, Yunling Ma, Lishan Qiao, Mingxia Liu:
Triplet Learning for Chest X-Ray Image Search in Automated COVID-19 Analysis. MLMI@MICCAI (2) 2023: 407-416 - [i15]Yuqi Fang, Pew-Thian Yap, Weili Lin, Hongtu Zhu, Mingxia Liu:
Source-Free Unsupervised Domain Adaptation: A Survey. CoRR abs/2301.00265 (2023) - [i14]Hao Guan, Mingxia Liu:
Federated Learning for Medical Image Analysis: A Survey. CoRR abs/2306.05980 (2023) - [i13]Lintao Zhang, Jinjian Wu, Lihong Wang, Li Wang, David C. Steffens, Shijun Qiu, Guy G. Potter, Mingxia Liu:
Brain Anatomy Prior Modeling to Forecast Clinical Progression of Cognitive Impairment with Structural MRI. CoRR abs/2306.11837 (2023) - [i12]Qianqian Wang, Wei Wang, Yuqi Fang, Pew-Thian Yap, Hongtu Zhu, Hong-Jun Li, Lishan Qiao, Mingxia Liu:
Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI. CoRR abs/2306.14080 (2023) - [i11]Junhao Zhang, Qianqian Wang, Xiaochuan Wang, Lishan Qiao, Mingxia Liu:
Preserving Specificity in Federated Graph Learning for fMRI-based Neurological Disorder Identification. CoRR abs/2308.10302 (2023) - [i10]Yuqi Fang, Jinjian Wu, Qianqian Wang, Shijun Qiu, Andrea Bozoki, Huaicheng Yan, Mingxia Liu:
Source-Free Collaborative Domain Adaptation via Multi-Perspective Feature Enrichment for Functional MRI Analysis. CoRR abs/2308.12495 (2023) - 2022
- [j78]Qianqian Wang, Long Li, Lishan Qiao, Mingxia Liu:
Adaptive Multimodal Neuroimage Integration for Major Depression Disorder Detection. Frontiers Neuroinformatics 16: 856175 (2022) - [j77]Hancan Zhu, Mingxia Liu, Zhenyu Tang, Shuai Wang:
Editorial: Weakly supervised deep learning-based methods for brain image analysis. Frontiers Neuroinformatics 16 (2022) - [j76]Shuai Han, Mingxia Liu, Jian-Zhong Li:
Efficient Partitioning Method for Optimizing the Compression on Array Data. J. Comput. Sci. Technol. 37(5): 1049-1067 (2022) - [j75]Hui Su, Limei Zhang, Lishan Qiao, Mingxia Liu:
Estimating high-order brain functional networks by correlation-preserving embedding. Medical Biol. Eng. Comput. 60(10): 2813-2823 (2022) - [j74]Yunbi Liu, Ling Yue, Shifu Xiao, Wei Yang, Dinggang Shen, Mingxia Liu:
Assessing clinical progression from subjective cognitive decline to mild cognitive impairment with incomplete multi-modal neuroimages. Medical Image Anal. 75: 102266 (2022) - [j73]Nan Wang, Dongren Yao, Lizhuang Ma, Mingxia Liu:
Multi-site clustering and nested feature extraction for identifying autism spectrum disorder with resting-state fMRI. Medical Image Anal. 75: 102279 (2022) - [j72]Mingliang Wang, Daoqiang Zhang, Jiashuang Huang, Mingxia Liu, Qingshan Liu:
Consistent connectome landscape mining for cross-site brain disease identification using functional MRI. Medical Image Anal. 82: 102591 (2022) - [j71]Yongsheng Pan, Ming-Xia Liu, Yong Xia, Dinggang Shen:
Disease-Image-Specific Learning for Diagnosis-Oriented Neuroimage Synthesis With Incomplete Multi-Modality Data. IEEE Trans. Pattern Anal. Mach. Intell. 44(10): 6839-6853 (2022) - [j70]Hao Guan, Mingxia Liu:
Domain Adaptation for Medical Image Analysis: A Survey. IEEE Trans. Biomed. Eng. 69(3): 1173-1185 (2022) - [j69]Chunfeng Lian, Mingxia Liu, Yongsheng Pan, Dinggang Shen:
Attention-Guided Hybrid Network for Dementia Diagnosis With Structural MR Images. IEEE Trans. Cybern. 52(4): 1992-2003 (2022) - [j68]Yu Zhang, Han Zhang, Ehsan Adeli, Xiaobo Chen, Mingxia Liu, Dinggang Shen:
Multiview Feature Learning With Multiatlas-Based Functional Connectivity Networks for MCI Diagnosis. IEEE Trans. Cybern. 52(7): 6822-6833 (2022) - [j67]Zhengdong Wang, Biao Jie, Chunxiang Feng, Taochun Wang, Weixin Bian, Xintao Ding, Wen Zhou, Mingxia Liu:
Distribution-Guided Network Thresholding for Functional Connectivity Analysis in fMRI-Based Brain Disorder Identification. IEEE J. Biomed. Health Informatics 26(4): 1602-1613 (2022) - [j66]Chunfeng Lian, Mingxia Liu, Li Wang, Dinggang Shen:
Multi-Task Weakly-Supervised Attention Network for Dementia Status Estimation With Structural MRI. IEEE Trans. Neural Networks Learn. Syst. 33(8): 4056-4068 (2022) - [c60]Qianqian Wang, Lishan Qiao, Mingxia Liu:
Function MRI Representation Learning via Self-supervised Transformer for Automated Brain Disorder Analysis. MLMI@MICCAI 2022: 1-10 - [c59]Minhui Yu, Hao Guan, Yuqi Fang, Ling Yue, Mingxia Liu:
Domain-Prior-Induced Structural MRI Adaptation for Clinical Progression Prediction of Subjective Cognitive Decline. MICCAI (1) 2022: 24-33 - [c58]Hao Guan, Siyuan Liu, Weili Lin, Pew-Thian Yap, Mingxia Liu:
Fast Image-Level MRI Harmonization via Spectrum Analysis. MLMI@MICCAI 2022: 201-209 - [c57]Lintao Zhang, Minhui Yu, Lihong Wang, David C. Steffens, Rong Wu, Guy G. Potter, Mingxia Liu:
Understanding Clinical Progression of Late-Life Depression to Alzheimer's Disease Over 5 Years with Structural MRI. MLMI@MICCAI 2022: 259-268 - [c56]Yuqi Fang, Jorge Daniel Oldan, Weili Lin, Travis Parke Schrank, Wendell Gray Yarbrough, Natalia Isaeva, Mingxia Liu:
Prediction of HPV-Associated Genetic Diversity for Squamous Cell Carcinoma of Head and Neck Cancer Based on 18F-FDG PET/CT. MLMI@MICCAI 2022: 358-366 - [c55]Ming-Xia Liu, Xiang Cheng, Sen Su, Ming Kuang, Gang Li:
Bootstrapping Joint Entity and Relation Extraction with Reinforcement Learning. WISE 2022: 418-432 - [i9]Hao Guan, Ling Yue, Pew-Thian Yap, Andrea Bozoki, Mingxia Liu:
Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI. CoRR abs/2206.12480 (2022) - [i8]Hao Guan, Mingxia Liu:
DomainATM: Domain Adaptation Toolbox for Medical Data Analysis. CoRR abs/2209.11890 (2022) - [i7]Lintao Zhang, Lihong Wang, Minhui Yu, Rong Wu, David C. Steffens, Guy G. Potter, Mingxia Liu:
Hybrid Representation Learning for Cognitive Diagnosis in Late-Life Depression Over 5 Years with Structural MRI. CoRR abs/2212.12810 (2022) - 2021
- [j65]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) - [j64]Ying Chu, Guangyu Wang, Liang Cao, Lishan Qiao, Mingxia Liu:
Multi-Scale Graph Representation Learning for Autism Identification With Functional MRI. Frontiers Neuroinformatics 15: 802305 (2021) - [j63]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) - [j62]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) - [j61]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) - [j60]Jun Zhang, Zhiyuan Hua, Kezhou Yan, Kuan Tian, Jianhua Yao, Eryun Liu, Mingxia Liu, Xiao Han:
Joint fully convolutional and graph convolutional networks for weakly-supervised segmentation of pathology images. Medical Image Anal. 73: 102183 (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]Jun Zhang, Mingxia Liu, Ke Lu, Yue Gao:
Group-Wise Learning for Aurora Image Classification With Multiple Representations. IEEE Trans. Cybern. 51(8): 4112-4124 (2021) - [j57]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) - [j56]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) - [j55]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) - [j54]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) - [c54]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 - [c53]Hao Guan, Li Wang, Mingxia Liu:
Multi-Source Domain Adaptation via Optimal Transport for Brain Dementia Identification. ISBI 2021: 1514-1517 - [c52]Hao Guan, Li Wang, Dongren Yao, Andrea Bozoki, Mingxia Liu:
Learning Transferable 3D-CNN for MRI-Based Brain Disorder Classification from Scratch: An Empirical Study. MLMI@MICCAI 2021: 10-19 - [c51]Yunbi Liu, Genggeng Qin, Yun Liu, Mingxia Liu, Wei Yang:
Improving Tuberculosis Recognition on Bone-Suppressed Chest X-Rays Guided by Task-Specific Features. PRIME@MICCAI 2021: 59-69 - [c50]Dongren Yao, Erkun Yang, Li Sun, Jing Sui, Mingxia Liu:
Integrating Multimodal MRIs for Adult ADHD Identification with Heterogeneous Graph Attention Convolutional Network. PRIME@MICCAI 2021: 157-167 - [c49]Dongren Yao, Erkun Yang, Hao Guan, Jing Sui, Zhizhong Zhang, Mingxia Liu:
Tensor-Based Multi-index Representation Learning for Major Depression Disorder Detection with Resting-State fMRI. MICCAI (5) 2021: 174-184 - [c48]Hao Guan, Yunbi Liu, Shifu Xiao, Ling Yue, Mingxia Liu:
Cost-Sensitive Meta-learning for Progress Prediction of Subjective Cognitive Decline with Brain Structural MRI. MICCAI (5) 2021: 248-258 - [c47]Kai Lin, Biao Jie, Peng Dong, Xintao Ding, Weixin Bian, Mingxia Liu:
Extracting Sequential Features from Dynamic Connectivity Network with rs-fMRI Data for AD Classification. MLMI@MICCAI 2021: 664-673 - [c46]Peng Dong, Biao Jie, Lin Kai, Xintao Ding, Weixin Bian, Mingxia Liu:
Integration of Handcrafted and Embedded Features from Functional Connectivity Network with rs-fMRI forBrain Disease Classification. MLMI@MICCAI 2021: 674-681 - [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
- [j53]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) - [j52]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) - [j51]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) - [j50]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) - [j49]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) - [j48]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) - [j47]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) - [j46]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) - [j45]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) - [j44]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) - [j43]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) - [j42]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) - [j41]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) - [j40]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
- [j39]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) - [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]