Alzheimer's disease classification using pre-trained deep networks
JV Shanmugam, B Duraisamy, BC Simon… - … Signal Processing and …, 2022 - Elsevier
Alzheimer disease (AD) is a progressive neurologic disorder that causes the brain to shrink
(atrophy) and brain cells to die. Alzheimer disease is the most common cause of dementia …
(atrophy) and brain cells to die. Alzheimer disease is the most common cause of dementia …
Disease inference from health-related questions via sparse deep learning
Automatic disease inference is of importance to bridge the gap between what online health
seekers with unusual symptoms need and what busy human doctors with biased expertise …
seekers with unusual symptoms need and what busy human doctors with biased expertise …
Classification of Alzheimer's disease subjects from MRI using hippocampal visual features
Indexing and classification tools for Content Based Visual Information Retrieval (CBVIR)
have been penetrating the universe of medical image analysis. They have been recently …
have been penetrating the universe of medical image analysis. They have been recently …
Recognition of Alzheimer's disease and Mild Cognitive Impairment with multimodal image-derived biomarkers and Multiple Kernel Learning
Abstract Computer-Aided Diagnosis (CAD) of Alzheimer's disease (AD) has drawn the
attention of computer vision research community over the last few years. Several attempts …
attention of computer vision research community over the last few years. Several attempts …
Alzheimer's disease diagnosis on structural MR images using circular harmonic functions descriptors on hippocampus and posterior cingulate cortex
Recently, several pattern recognition methods have been proposed to automatically
discriminate between patients with and without Alzheimer's disease using different imaging …
discriminate between patients with and without Alzheimer's disease using different imaging …
Alzheimer disease detection from structural MR images using FCM based weighted probabilistic neural network
B Duraisamy, JV Shanmugam, J Annamalai - Brain imaging and behavior, 2019 - Springer
An early intervention of Alzheimer's disease (AD) is highly essential due to the fact that this
neuro degenerative disease generates major life-threatening issues, especially memory …
neuro degenerative disease generates major life-threatening issues, especially memory …
An efficient classification approach for detection of Alzheimer's disease from biomedical imaging modalities
The complex patterns of the neuroimaging data are analyzed successfully with bio-medical
imaging applications. The patients with/without AD can be discriminated effectively through …
imaging applications. The patients with/without AD can be discriminated effectively through …
Earlier detection of Alzheimer disease using N-fold cross validation approach
According to the recent study, world-wide 40 million patients are affected by Alzheimer
disease (AD) because it is one of the dangerous neurodegenerative disorders. This AD …
disease (AD) because it is one of the dangerous neurodegenerative disorders. This AD …
3-1-3 Weight averaging technique-based performance evaluation of deep neural networks for Alzheimer's disease detection using structural MRI
Alzheimer's disease (AD) is a progressive neurological disorder. It is identified by the
gradual shrinkage of the brain and the loss of brain cells. This leads to cognitive decline and …
gradual shrinkage of the brain and the loss of brain cells. This leads to cognitive decline and …
Longitudinal brain MRI retrieval for Alzheimer's disease using different temporal information
This paper describes the research made toward improving medical case retrieval for
Alzheimer's Disease (AD). Our approach considers using Magnetic Resonance Images as …
Alzheimer's Disease (AD). Our approach considers using Magnetic Resonance Images as …