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Computer Science

D-Index
53
Citations
9431
World Ranking
4894
National Ranking
2273

Overview

Mingxia Liu is affiliated with the University of North Carolina at Chapel Hill in the United States. Their research primarily focuses on applications within medicine and neuroscience, with significant contributions intersecting cognitive neuroscience, radiology, nuclear medicine and imaging, artificial intelligence, computer vision and pattern recognition, and neurology.

The scientist's work covers several specialized topics, including functional brain connectivity studies, advanced MRI techniques and applications, advanced neuroimaging techniques and applications, EEG and brain-computer interfaces, brain tumor detection and classification, radiomics and machine learning in medical imaging, as well as domain adaptation and few-shot learning.

Recent publications by Mingxia Liu include:

  • Federated learning for medical image analysis: A survey, 2024, published in Pattern Recognition
  • A Survey on Deep Learning for Neuroimaging-Based Brain Disorder Analysis, 2020, published in Frontiers in Neuroscience
  • A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity, 2021, published in IEEE Transactions on Medical Imaging
  • Multi-site MRI harmonization via attention-guided deep domain adaptation for brain disorder identification, 2021, published in Medical Image Analysis
  • Disease-Image-Specific Learning for Diagnosis-Oriented Neuroimage Synthesis With Incomplete Multi-Modality Data, 2021, published in IEEE Transactions on Pattern Analysis and Machine Intelligence

Mingxia Liu frequently collaborates with a group of coauthors, including Dinggang Shen, Pew-Thian Yap, Lishan Qiao, Daoqiang Zhang, and Yuqi Fang.

Their publications have appeared predominantly in venues such as:

  • UNC Libraries
  • arXiv (Cornell University)
  • Medical Image Analysis
  • Lecture Notes in Computer Science
  • SSRN Electronic Journal

Best Publications

  • Domain Adaptation for Medical Image Analysis: A Survey

    Hao Guan;Mingxia Liu

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

    Chunfeng Lian;Mingxia Liu;Jun Zhang;Dinggang Shen

  • Landmark-based deep multi-instance learning for brain disease diagnosis

    Mingxia Liu;Jun Zhang;Ehsan Adeli;Dinggang Shen;Dinggang Shen

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

    Mingxia Liu;Jun Zhang;Ehsan Adeli;Dinggang Shen

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

    Li Zhang;Li Zhang;Mingliang Wang;Mingxia Liu;Daoqiang Zhang

  • Relationship Induced Multi-Template Learning for Diagnosis of Alzheimer’s Disease and Mild Cognitive Impairment

    Mingxia Liu;Daoqiang Zhang;Dinggang Shen

  • Latent Representation Learning for Alzheimer’s Disease Diagnosis With Incomplete Multi-Modality Neuroimaging and Genetic Data

    Tao Zhou;Mingxia Liu;Kim-Han Thung;Dinggang Shen

  • Domain Transfer Learning for MCI Conversion Prediction

    Bo Cheng;Mingxia Liu;Daoqiang Zhang;Brent C. Munsell

  • Detecting Anatomical Landmarks From Limited Medical Imaging Data Using Two-Stage Task-Oriented Deep Neural Networks

    Jun Zhang;Mingxia Liu;Dinggang Shen

  • Synthesizing Missing PET from MRI with Cycle-consistent Generative Adversarial Networks for Alzheimer's Disease Diagnosis.

    Yongsheng Pan;Mingxia Liu;Chunfeng Lian;Tao Zhou

  • Alzheimer's Disease Diagnosis Using Landmark-Based Features From Longitudinal Structural MR Images.

    Jun Zhang;Mingxia Liu;Le An;Yaozong Gao

  • Integration of temporal and spatial properties of dynamic connectivity networks for automatic diagnosis of brain disease

    Biao Jie;Biao Jie;Mingxia Liu;Dinggang Shen;Dinggang Shen

  • Inherent Structure-Based Multiview Learning With Multitemplate Feature Representation for Alzheimer's Disease Diagnosis

    Mingxia Liu;Daoqiang Zhang;Ehsan Adeli;Dinggang Shen

  • Anatomical Landmark Based Deep Feature Representation for MR Images in Brain Disease Diagnosis

    Mingxia Liu;Jun Zhang;Dong Nie;Pew-Thian Yap

  • Identifying Autism Spectrum Disorder With Multi-Site fMRI via Low-Rank Domain Adaptation

    Mingliang Wang;Daoqiang Zhang;Jiashuang Huang;Pew-Thian Yap

  • 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

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

    Yingkun Hou;Jun Xu;Mingxia Liu;Guanghai Liu

  • View-aligned hypergraph learning for Alzheimer's disease diagnosis with incomplete multi-modality data

    Mingxia Liu;Jun Zhang;Pew Thian Yap;Dinggang Shen;Dinggang Shen

  • Two-Stage Cost-Sensitive Learning for Software Defect Prediction

    Mingxia Liu;Linsong Miao;Daoqiang Zhang

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

    Mingliang Wang;Chunfeng Lian;Dongren Yao;Daoqiang Zhang

  • Strength and Similarity Guided Group-level Brain Functional Network Construction for MCI Diagnosis.

    Yu Zhang;Yu Zhang;Han Zhang;Xiaobo Chen;Mingxia Liu

  • Multi-channel multi-scale fully convolutional network for 3D perivascular spaces segmentation in 7T MR images.

    Chunfeng Lian;Jun Zhang;Mingxia Liu;Xiaopeng Zong

  • View‐centralized multi‐atlas classification for Alzheimer's disease diagnosis

    Mingxia Liu;Daoqiang Zhang;Dinggang Shen;Alzheimer's Disease Neuroimaging Initiative

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Daoqiang Zhang
Daoqiang Zhang Nanjing University of Aeronautics and Astronautics
Pew Thian Yap
Pew Thian Yap University of North Carolina at Chapel Hill
Ehsan Adeli
Ehsan Adeli Stanford University
Feng Shi
Feng Shi United Imaging Intelligence (China)
Yong Xia
Yong Xia Northwestern Polytechnical University
Jing Sui
Jing Sui Beijing Normal University
Han Zhang
Han Zhang ShanghaiTech University
Songcan Chen
Songcan Chen Nanjing University of Aeronautics and Astronautics
Wei Yang
Wei Yang Southern Medical University

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