Brain-on-Cloud for automatic diagnosis of Alzheimer's disease from 3D structural magnetic resonance whole-brain scans

S Tomassini, A Sbrollini, G Covella, P Sernani… - Computer Methods and …, 2022 - Elsevier
Background and objective Alzheimer's disease accounts for approximately 70% of all
dementia cases. Cortical and hippocampal atrophy caused by Alzheimer's disease can be …

An end-to-end 3D ConvLSTM-based framework for early diagnosis of Alzheimer's disease from full-resolution whole-brain sMRI scans

S Tomassini, N Falcionelli, P Sernani… - 2021 IEEE 34th …, 2021 - ieeexplore.ieee.org
Alzheimer's Disease (AD) is the most prevailing form of dementia, killing more people than
prostate and breast cancers combined. Structural Magnetic Resonance Imaging (sMRI) is …

Deep convolutional neural networks for automated diagnosis of Alzheimer's disease and mild cognitive impairment using 3D brain MRI

J Islam, Y Zhang… - … Conference, BI 2018 …, 2018 - Springer
We consider the automated diagnosis of Alzheimer's Disease (AD) and Mild Cognitive
Impairment (MCI) in 3D structural MRI brain scans. We develop an efficient deep …

A fast and accurate 3D fine-tuning convolutional neural network for Alzheimer's disease diagnosis

H Tang, E Yao, G Tan, X Guo - … , ICAI 2018, Jinan, China, August 9-10 …, 2018 - Springer
The fast and accurate diagnosis of Alzheimer's Disease (AD) plays a significant part in
patient care, especially at the early stage. The main difficulty lies in the three-class …

Early identification of Alzheimer's disease using an ensemble of 3D convolutional neural networks and magnetic resonance imaging

Y Chen, H Jia, Z Huang, Y Xia - … in Brain Inspired Cognitive Systems: 9th …, 2018 - Springer
Alzheimer's disease (AD) has become a nonnegligible global health threat and social
problem as the world population ages. The ability to identify AD subjects in an early stage …

Alzheimer's disease diagnostics by a deeply supervised adaptable 3D convolutional network

E Hosseini-Asl, G Gimel'farb, A El-Baz - arXiv preprint arXiv:1607.00556, 2016 - arxiv.org
Early diagnosis, playing an important role in preventing progress and treating the
Alzheimer's disease (AD), is based on classification of features extracted from brain images …

3d Convolutional neural networks for diagnosis of alzheimer's disease via structural mri

E Yagis, L Citi, S Diciotti, C Marzi… - 2020 IEEE 33rd …, 2020 - ieeexplore.ieee.org
Alzheimer's Disease (AD) is a widespread neurodegenerative disease caused by structural
changes in the brain and leads to deterioration of cognitive functions. Patients usually …

Multi-scale attention-based pseudo-3D convolution neural network for Alzheimer's disease diagnosis using structural MRI

Z Pei, Z Wan, Y Zhang, M Wang, C Leng, YH Yang - Pattern Recognition, 2022 - Elsevier
Recently, deep learning based Computer-Aided Diagnosis methods have been widely
utilized due to their highly effective diagnosis of patients. Although Convolutional Neural …

Detection of subjects and brain regions related to Alzheimer's disease using 3D MRI scans based on eigenbrain and machine learning

Y Zhang, Z Dong, P Phillips, S Wang, G Ji… - Frontiers in …, 2015 - frontiersin.org
Purpose: Early diagnosis or detection of Alzheimer's disease (AD) from the normal elder
control (NC) is very important. However, the computer-aided diagnosis (CAD) was not …

BG-3DM2F: Bidirectional gated 3D multi-scale feature fusion for Alzheimer's disease diagnosis

I Bakkouri, K Afdel, J Benois-Pineau… - Multimedia Tools and …, 2022 - Springer
A computer-aided diagnosis system is one of the crucial decision support tools under the
medical imaging scope. It has recently emerged as a powerful way to diagnose Alzheimer's …