mlsanityData to 7 Oct 2026

Predicting Alzheimer's disease: a neuroimaging study with 3D convolutional neural networks

arXiv 1502.02506 ↗First posted 9 Feb 2015cs.CV cs.LG stat.APcited by 17

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Abstract (arXiv)

Pattern recognition methods using neuroimaging data for the diagnosis of Alzheimer's disease have been the subject of extensive research in recent years. In this paper, we use deep learning methods, and in particular sparse autoencoders and 3D convolutional neural networks, to build an algorithm that can predict the disease status of a patient, based on an MRI scan of the brain. We report on experiments using the ADNI data set involving 2,265 historical scans. We demonstrate that 3D convolutional neural networks outperform several other classifiers reported in the literature and produce state-of-art results.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Feb 2015.

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Citing papers per year: 2021: 3; 2022: 3; 2023: 7; 2024: 2; 2025: 0; 2026: 2.

17 papers.

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  1. 2022Is a PET all you need? A multi-modal study for Alzheimer's disease using 3D CNNscited by 11
  2. 2021Deep Learning in current Neuroimaging: a multivariate approach with power and type I error control but arguable generalization abilitycited by 4
  3. 2023Promises and pitfalls of deep neural networks in neuroimaging-based psychiatric researchcited by 4
  4. 2022Biceph-Net: A robust and lightweight framework for the diagnosis of Alzheimer's disease using 2D-MRI scans and deep similarity learningcited by 3
  5. 2024Multi-scale fMRI time series analysis for understanding neurodegeneration in MCIcited by 3
  6. 2024Enhancing MRI-Based Classification of Alzheimer's Disease with Explainable 3D Hybrid Compact Convolutional Transformerscited by 3
  7. 2023Looking deeper into interpretable deep learning in neuroimaging: a comprehensive surveycited by 2
  8. 2021BRAIN2DEPTH: Lightweight CNN Model for Classification of Cognitive States from EEG Recordingscited by 1
  9. 2023Deep Learning in Healthcare: An In-Depth Analysiscited by 1
  10. 2021Automatic detection of impact craters on Al foils from the Stardust interstellar dust collector using convolutional neural networkscited by 0
  11. 2022An overview of deep learning in medical imagingcited by 0
  12. 2023Transfer Learning and Class Decomposition for Detecting the Cognitive Decline of Alzheimer Diseasecited by 0
5 more
  1. 2023Medical Image Analysis using Deep Relational Learningcited by 0
  2. 2023Convolutional Neural Networks for Neuroimaging in Parkinson's Disease: Is Preprocessing Needed?cited by 0
  3. 2023Multimodal Identification of Alzheimer's Disease: A Reviewcited by 0
  4. 2026Alzheimer's Disease Diagnosis using a Multimodal Approach with 3D MRI and PETcited by 0
  5. 2026Comparative Study of Anatomical and Learned Features in AI Models for Structural Brain MRIcited by 0