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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
- Mingxia Liu 0004 — Shenyang Center for Urban and Rural Construction, Department of Rail Transportation Affairs, China
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2020 – today
- 2025
[j96]Xiaochuan Wang
, Yuqi Fang, Qianqian Wang, Pew-Thian Yap, Hongtu Zhu, Mingxia Liu:
Self-supervised graph contrastive learning with diffusion augmentation for functional MRI analysis and brain disorder detection. Medical Image Anal. 101: 103403 (2025)- [j95]Yuqi Fang, Junhao Zhang, Linmin Wang, Qianqian Wang, Mingxia Liu:
ACTION: Augmentation and computation toolbox for brain network analysis with functional MRI. NeuroImage 305: 120967 (2025) - [j94]Wenyang Li, Mingliang Wang, Mingxia Liu, Qingshan Liu:
Riemannian manifold-based disentangled representation learning for multi-site functional connectivity analysis. Neural Networks 183: 106945 (2025) - [j93]Mengqi Wu, Lintao Zhang, Pew-Thian Yap, Hongtu Zhu, Mingxia Liu:
Disentangled latent energy-based style translation: An image-level structural MRI harmonization framework. Neural Networks 184: 107039 (2025) - [j92]Zhiming Cheng, Mingxia Liu, Chenggang Yan, Shuai Wang:
Dynamic domain generalization for medical image segmentation. Neural Networks 184: 107073 (2025) - [j91]Minhui Yu, Yuqi Fang, Yunbi Liu, Andrea C. Bozoki, Shifu Xiao, Ling Yue, Mingxia Liu:
Hybrid multi-modality multi-task learning for forecasting progression trajectories in subjective cognitive decline. Neural Networks 186: 107263 (2025) - [j90]Yuqi Fang, Jinjian Wu, Qianqian Wang, Shijun Qiu, Andrea Bozoki, Mingxia Liu:
Source-free collaborative domain adaptation via multi-perspective feature enrichment for functional MRI analysis. Pattern Recognit. 157: 110912 (2025) - 2024
- [j89]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. Medical Image Anal. 94: 103135 (2024) - [j88]Junhao Zhang, Qianqian Wang, Xiaochuan Wang, Lishan Qiao, Mingxia Liu:
Preserving specificity in federated graph learning for fMRI-based neurological disorder identification. Neural Networks 169: 584-596 (2024) - [j87]Linmin Wang, Qianqian Wang, Xiaochuan Wang, Yunling Ma, Limei Zhang, Mingxia Liu:
Triplet-constrained deep hashing for chest X-ray image retrieval in COVID-19 assessment. Neural Networks 173: 106182 (2024) - [j86]Yuqi Fang, Pew-Thian Yap, Weili Lin, Hongtu Zhu, Ming-Xia Liu:
Source-free unsupervised domain adaptation: A survey. Neural Networks 174: 106230 (2024) - [j85]Chaojun Zhang, Yunling Ma, Lishan Qiao, Limei Zhang, Mingxia Liu:
Learning functional brain networks with heterogeneous connectivities for brain disease identification. Neural Networks 180: 106660 (2024) - [j84]Hao Guan, Pew-Thian Yap, Andrea Bozoki, Mingxia Liu:
Federated learning for medical image analysis: A survey. Pattern Recognit. 151: 110424 (2024) - [j83]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. IEEE Trans. Biomed. Eng. 71(8): 2391-2401 (2024) - [j82]Guangyu Wang, Ying Chu, Qianqian Wang, Limei Zhang, Lishan Qiao, Mingxia Liu:
Graph Convolutional Network With Self-Supervised Learning for Brain Disease Classification. IEEE ACM Trans. Comput. Biol. Bioinform. 21(6): 1830-1841 (2024) - [c68]Yuqi Fang, Wei Wang, Qianqian Wang, Hong-Jun Li, Mingxia Liu:
Attention-Enhanced Fusion of Structural and Functional MRI for Analyzing HIV-Associated Asymptomatic Neurocognitive Impairment. MICCAI (11) 2024: 113-123 - [i24]Mengqi Wu, Lintao Zhang, Pew-Thian Yap, Hongtu Zhu, Mingxia Liu:
Disentangled Latent Energy-Based Style Translation: An Image-Level Structural MRI Harmonization Framework. CoRR abs/2402.06875 (2024) - [i23]Lintao Zhang, Mengqi Wu, Lihong Wang, David C. Steffens, Guy G. Potter, Mingxia Liu:
Iterative Learning for Joint Image Denoising and Motion Artifact Correction of 3D Brain MRI. CoRR abs/2403.08162 (2024) - [i22]Minhui Yu, Mengqi Wu, Ling Yue, Andrea Bozoki, Mingxia Liu:
Functional Imaging Constrained Diffusion for Brain PET Synthesis from Structural MRI. CoRR abs/2405.02504 (2024) - [i21]Yuqi Fang, Junhao Zhang, Linmin Wang, Qianqian Wang, Mingxia Liu:
ACTION: Augmentation and Computation Toolbox for Brain Network Analysis with Functional MRI. CoRR abs/2405.06178 (2024) - [i20]Yunling Ma, Chaojun Zhang, Xiaochuan Wang, Qianqian Wang, Liang Cao, Limei Zhang, Mingxia Liu:
Augmentation-based Unsupervised Cross-Domain Functional MRI Adaptation for Major Depressive Disorder Identification. CoRR abs/2406.00085 (2024) - [i19]Mengqi Wu, Minhui Yu, Shuaiming Jing, Pew-Thian Yap, Zhengwu Zhang, Mingxia Liu:
Unpaired Volumetric Harmonization of Brain MRI with Conditional Latent Diffusion. CoRR abs/2408.09315 (2024) - [i18]Yongheng Sun, Yueh Z. Lee, Genevieve A. Woodard, Hongtu Zhu, Chunfeng Lian, Mingxia Liu:
R2Gen-Mamba: A Selective State Space Model for Radiology Report Generation. CoRR abs/2410.18135 (2024) - [i17]Yongheng Sun, Mingxia Liu, Chunfeng Lian:
AEPL: Automated and Editable Prompt Learning for Brain Tumor Segmentation. CoRR abs/2410.19847 (2024) - [i16]Qianqian Wang, Wei Wang, Yuqi Fang, Hong-Jun Li, Andrea Bozoki, Mingxia Liu:
Topology-Aware Graph Augmentation for Predicting Clinical Trajectories in Neurocognitive Disorders. CoRR abs/2411.00888 (2024) - 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) - [c67]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 - [c66]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 - [c65]Minhui Yu, Yunbi Liu, Jinjian Wu, Andrea Bozoki, Shijun Qiu, Ling Yue, Mingxia Liu:
Hybrid Multimodality Fusion with Cross-Domain Knowledge Transfer to Forecast Progression Trajectories in Cognitive Decline. MTSAIL/LEAF/AI4Treat/MMMI/REMIA@MICCAI 2023: 265-275 - [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]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 - [c18]Ti-Wei Tao, De-Yun Yang, Lin-Lin Wang, Ming-Xia Liu:
Effective Distance based Low Rank Representation for Image Classification. SPAC 2018: 460-464 - [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) - [c17]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 - [c16]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 - [c15]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) - [c14]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 - [c13]Biao Jie, Mingxia Liu, Xi Jiang, Daoqiang Zhang:
Sub-network Based Kernels for Brain Network Classification. BCB 2016: 622-629 - [c12]Mingxia Liu, Junqiang Du, Biao Jie, Daoqiang Zhang:
Ordinal Patterns for Connectivity Networks in Brain Disease Diagnosis. MICCAI (1) 2016: 1-9 - [c11]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 - [c10]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 - [c9]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 - 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]Mingxia Liu, Daoqiang Zhang:
Sparsity Score: a Novel Graph-Preserving Feature Selection Method. Int. J. Pattern Recognit. Artif. Intell. 28(4) (2014) - [j3]Mingxia Liu, Linsong Miao, Daoqiang Zhang:
Two-Stage Cost-Sensitive Learning for Software Defect Prediction. IEEE Trans. Reliab. 63(2): 676-686 (2014) - 2012
- [c5]Mingxia Liu, Dan Sun, Daoqiang Zhang:
Sparsity Score: A new filter feature selection method based on graph. ICPR 2012: 959-962 - [c4]Linsong Miao, Mingxia Liu, Daoqiang Zhang:
Cost-sensitive feature selection with application in software defect prediction. ICPR 2012: 967-970 - [c3]Mingxia Liu, Songcan Chen, Daoqiang Zhang:
Learning Attribute Relation in Attribute-Based Zero-Shot Classification. IScIDE 2012: 514-521 - 2010
- [j2]Shengju Sang, Mingxia Liu, Jing Liu, Qi An:
A new approach for texture classification in CBIR. Int. J. Comput. Appl. Technol. 38(1/2/3): 34-39 (2010) - [j1]Yingkun Hou, Chunxia Zhao, Mingxia Liu, Zhengli Zhu, Deyun Yang:
Semisubsampled Wavelet Transform Based Image Watermarking with Strong Robustness to Rotation Attacks. J. Multim. 5(4): 385-392 (2010)
2000 – 2009
- 2008
- [c2]Yingkun Hou, Chunxia Zhao, Mingxia Liu, Deyun Yang:
The Nonsubsampled Contourlet-Wavelet Hybrid Transform: Design and Application to Image Watermarking. CSSE (3) 2008: 627-630 - 2007
- [c1]Yingkun Hou, Xiangcai Zhu, Zhu Lili, Mingxia Liu:
Image with Less Information Watermarking Algorithm Based on DWT. SNPD (3) 2007: 383-387
Coauthor Index
[j74] [j71] [j69] [j68] [j66] [j61] [j59] [j56] [j55] [j54] [j53] [j52] [j51] [j49] [j48] [j46] [j43] [j42] [j40] [c44] [c43] [c42] [c41] [c40] [c38] [c37] [i3] [j37] [j35] [j34] [j33] [j32] [j31] [j30] [c35] [c34] [c33] [c32] [c31] [c30] [c29] [c28] [c27] [j28] [j27] [j26] [j24] [j23] [j22] [c26] [c25] [c24] [c23] [c22] [c21] [c20] [j17] [j16] [j15] [j14] [j13] [c17] [c16] [c15] [j9] [j7] [c11] [c10] [c9] [j6] [c8] [c6]
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