Automated classification of Alzheimer's disease, mild cognitive impairment, and cognitively normal patients using 3D convolutional neural network and radiomic features from T1-weighted brain MRI: A comparative study on detection accuracy.
Amin ZareiAhmad KeshavarzEsmail JafariReza NematiAkram FarhadiAli GholamrezanezhadHabib RostamiMajid AssadiPublished in: Clinical imaging (2024)
This study proposed an automated procedures based on MRI-derived radiomic features and CNN for classification between AD, MCI and CN.
Keyphrases
- mild cognitive impairment
- deep learning
- convolutional neural network
- cognitive decline
- contrast enhanced
- machine learning
- end stage renal disease
- magnetic resonance imaging
- newly diagnosed
- chronic kidney disease
- magnetic resonance
- prognostic factors
- diffusion weighted imaging
- resting state
- white matter
- functional connectivity
- lymph node metastasis
- blood brain barrier
- single cell
- network analysis
- label free