Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images from ADNI, AIBL, OASIS, and MIRIAD databases

Eitemau Tebyg

• Quantifying brain metabolism from FDG‐PET images into a probability of Alzheimer's dementia score
  gan: Yee, Evangeline, et al.
  Cyhoeddwyd: (2019)
• Quantitative assessment of field strength, total intracranial volume, sex, and age effects on the goodness of harmonization for volumetric analysis on the ADNI database
  gan: Ma, Da, et al.
  Cyhoeddwyd: (2018)
• Differential Diagnosis of Frontotemporal Dementia, Alzheimer's Disease, and Normal Aging Using a Multi-Scale Multi-Type Feature Generative Adversarial Deep Neural Network on Structural Magnetic Resonance Images
  gan: Ma, Da, et al.
  Cyhoeddwyd: (2020)
• Differential Diagnosis of Frontotemporal Dementia, Alzheimer's Disease, and Normal Aging Using a Multi-Scale Multi-Type Feature Generative Adversarial Deep Neural Network on Structural Magnetic Resonance Images
  gan: Da Ma, et al.
  Cyhoeddwyd: (2020-10-01)
• Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images
  gan: Lu, Donghuan, et al.
  Cyhoeddwyd: (2018)