mlsanityData to 14 Oct 2026

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

arXiv 2005.04573 ↗First posted 10 May 2020eess.IV cs.CV cs.LGcited by 27

Not on the map. Why?

Abstract (arXiv)

Deep learning has been recently used for the analysis of neuroimages, such as structural magnetic resonance imaging (MRI), functional MRI, and positron emission tomography (PET), and has achieved significant performance improvements over traditional machine learning in computer-aided diagnosis of brain disorders. This paper reviews the applications of deep learning methods for neuroimaging-based brain disorder analysis. We first provide a comprehensive overview of deep learning techniques and popular network architectures, by introducing various types of deep neural networks and recent developments. We then review deep learning methods for computer-aided analysis of four typical brain disorders, including Alzheimer's disease, Parkinson's disease, Autism spectrum disorder, and Schizophrenia, where the first two diseases are neurodegenerative disorders and the last two are neurodevelopmental and psychiatric disorders, respectively. More importantly, we discuss the limitations of existing studies and present possible future directions.

Key facts. Cited by 27 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 May 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 5; 2022: 8; 2023: 7; 2024: 5; 2025: 0; 2026: 2.

27 papers.

Sort:

  1. 2021Video Summarization Using Deep Neural Networks: A Surveycited by 85
  2. 2021Graph-Based Deep Learning for Medical Diagnosis and Analysis: Past, Present and Futurecited by 67
  3. 2023A Deep Neural Architecture for Harmonizing 3-D Input Data Analysis and Decision Making in Medical Imagingcited by 39
  4. 2021Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attackcited by 15
  5. 2022Generalisability of fetal ultrasound deep learning models to low-resource imaging settings in five African countriescited by 15
  6. 2022Deep Learning for Brain Age Estimation: A Systematic Reviewcited by 13
  7. 2023Intuitionistic Fuzzy Broad Learning System: Enhancing Robustness Against Noise and Outlierscited by 13
  8. 2021Applications of Deep Learning Techniques for Automated Multiple Sclerosis Detection Using Magnetic Resonance Imaging: A Reviewcited by 10
  9. 2023Multi-modal Graph Neural Network for Early Diagnosis of Alzheimer's Disease from sMRI and PET Scanscited by 9
  10. 2021Brain Multigraph Prediction using Topology-Aware Adversarial Graph Neural Networkcited by 8
  11. 2022Modern Views of Machine Learning for Precision Psychiatrycited by 5
  12. 2024Empowering Healthcare through Privacy-Preserving MRI Analysiscited by 4
15 more
  1. 2023A Deep Probabilistic Spatiotemporal Framework for Dynamic Graph Representation Learning with Application to Brain Disorder Identificationcited by 3
  2. 2024Advancing Brain Imaging Analysis Step-by-step via Progressive Self-paced Learningcited by 3
  3. 2022Pose-based Tremor Classification for Parkinson's Disease Diagnosis from Videocited by 2
  4. 2024Flexi-Fuzz least squares SVM for Alzheimer's diagnosis: Tackling noise, outliers, and class imbalancecited by 2
  5. 2022XADLiME: eXplainable Alzheimer's Disease Likelihood Map Estimation via Clinically-guided Prototype Learningcited by 1
  6. 2022Prediction of Gender from Longitudinal MRI data via Deep Learning on Adolescent Data Reveals Unique Patterns Associated with Brain Structure and Change over a Two-year Periodcited by 1
  7. 2023Pose-based Tremor Type and Level Analysis for Parkinson's Disease from Videocited by 1
  8. 2024Discovering robust biomarkers of psychiatric disorders from resting-state functional MRI via graph neural networks: A systematic reviewcited by 1
  9. 2022Improving the Level of Autism Discrimination through GraphRNN Link Predictioncited by 0
  10. 2022Learning Generative Factors of EEG Data with Variational auto-encoderscited by 0
  11. 2023Deep learning reveals the common spectrum underlying multiple brain disorders in youth and elders from brain functional networkscited by 0
  12. 2023Empowering Precision Medicine: AI-Driven Schizophrenia Diagnosis via EEG Signals: A Comprehensive Review from 2002-2023cited by 0
  13. 2024DyMix: Dynamic Frequency Mixup Scheduler based Unsupervised Domain Adaptation for Enhancing Alzheimer's Disease Identificationcited by 0
  14. 2026Joint Imaging-ROI Representation Learning via Cross-View Contrastive Alignment for Brain Disorder Classificationcited by 0
  15. 2026Multimodal Connectome Fusion via Cross-Attention for Autism Spectrum Disorder Classification Using Graph Learningcited by 0