ArticleArabian journal for science and engineering2023
Hippocampus Segmentation-Based Alzheimer's Disease Diagnosis and Classification of MRI Images.
Article in Arabian journal for science and engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 66 citations in OpenAlex.
- Deep learning-based cognitive impairment brain imaging analysis: New methods, new technologies, and new paradigms.Neural regeneration research · 2026Article
- ACross-Paradigm CNN-Swin Transformer Ensemble with Super-Resolution Enhancement for Multi-Class Alzheimer's Disease Classification.Bioengineering (Basel, Switzerland) · 2026Article
- Subregional limbic radiomics on FDG-PET provides accurate early detection of Alzheimer's disease.BMC medical imaging · 2026Article
- BrainNeXt: novel lightweight CNN model for the automated detection of brain disorders using MRI images.Cognitive neurodynamics · 2025Article
- A hybrid learning approach for MRI-based detection of alzheimer's disease stages using dual CNNs and ensemble classifier.Scientific reports · 2025Article
- Recent Advancements in Neuroimaging-Based Alzheimer's Disease Prediction Using Deep Learning Approaches in e-Health: A Systematic Review.Health science reports · 2025Review
- Advances in the use of structural and diffusion magnetic resonance imaging for characterizing SCD and MCI due to Alzheimer's disease.Frontiers in neuroscience · 2025Review
- Alzheimer's disease classification using a hybrid deep learning approach with multi-layer U-net segmentation and XAI driven analysis.PloS one · 2025Article
- Novel deep learning for multi-class classification of Alzheimer's in disability using MRI datasets.Frontiers in bioinformatics · 2025Article
- Research Progress on the Pathogenesis, Diagnosis, and Drug Therapy of Alzheimer's Disease.Brain sciences · 2024Review
- Advanced interpretable diagnosis of Alzheimer's disease using SECNN-RF framework with explainable AI.Frontiers in artificial intelligence · 2024Article
- A combinatorial deep learning method for Alzheimer's disease classification-based merging pretrained networks.Frontiers in computational neuroscience · 2024Article
- Accurate Detection of Alzheimer's Disease Using Lightweight Deep Learning Model on MRI Data.Diagnostics (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Alzheimer's disease represents a neurological condition characterized by steady cognitive decline and eventual memory loss due to the death of brain cells. It is one of the most prominent dementia types observed in patients and which hence underlines the imminent need for potential methods to diagnose the disease early on. This work considers a novel approach by utilizing a reduced version of one of the datasets used in this work to achieve a considerably accurate prediction while also enabling quicker training. It leverages image segmentation to isolate the hippocampus region from brain MRI images and then strikes a comparison between models trained on the segmented portions and models trained on complete images. This research uses two datasets-4 classes of images from Kaggle and a popular OASIS 2 MRI and demographic dataset. A deep learning-based approach was adopted to train the Kaggle dataset to perform severity classification, and the hippocampus region segmented from a reduced version of the OASIS dataset was trained on supervised and ensemble learning algorithms to detect Alzheimer's disease. The metric used for the assessment of model performance is classification accuracy. A comparative analysis between the proposed approach and existing work was also performed, and it was observed that the proposed approach is effective in the early diagnosis of Alzheimer's disease.
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