Can I read Multi-modality MRI for Alzheimer’s disease detection using deep learning on EtoBox?

Multi-modality MRI for Alzheimer’s disease detection using deep learning by Latifa Houria; Noureddine Belkhamsa; Assia Cherfa; Yazid Cherfa is a Medicine article available to read on EtoBox.

What is Multi-modality MRI for Alzheimer’s disease detection using deep learning about?

Diffusion tensor imaging (DTI) is a new technology in magnetic resonance imaging, which allows us to observe the insightful structure of the human body in vivo and non-invasively. It identifies the microstructure of white matter (WM) connectivity by estimating the movement of water molecules at each voxel. This makes possible the identification of the damage to WM integrity caused by Alzheimer's disease (AD) at its early stage, called mild cognitive impairment (MCI). Furthermore, the brain's gray matter (GM) atrophy characterizes the main structural changes in AD, which can be sensitively detected by structural MRI (sMRI) modality. In this research, we aimed to classify the Alzheimer's diseases stages by developing a novel multi-modality MRI (DTI and sMRI) fusion strategy to detect WM alterations and GM atrophy in AD patients. The latter is based on a 2-dimensional deep convolutional neural network (CNN) features extractor and a support vector machine (SVM) classifier. The fusion framework consists of merging features extracted from DTI scalar metrics [(fractional anisotropy (FA) and mean diffusivity (MD)], and GM using 2D-CNN and feeding them to SVM to classify AD versus cognitive

Who reads Multi-modality MRI for Alzheimer’s disease detection using deep learning?

Author

Latifa Houria; Noureddine Belkhamsa; Assia Cherfa; Yazid Cherfa

Publisher

Springer Science and Business Media LLC

Published

2022

Language

EN

Field

Medicine (Health Sciences)