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Here is the documentation about the construction and methods used in medical image classification with MRI and 3D convolutional nueral networks. It's important to you'd been prior expirience with neuroscience software as ANTs, SPM12, FREESURFER, FSL or even Nipype among others. As a general view the project has 3 stages: Preprocessing pipeline development, model construction and trainning and interpretability analysis
Project aim is to design a non-invasive diagnosis tool for Alzheimer's disease using software implementation in MATLAB.
Identifying Genetically Related Neuroimaging Biomarkers of Alzheimer's Disease via a Diagnosis-Guided Group Sparse Multitask Learning Method
Alzheimer’s disease detection by EEGSignal Processing and Supervised Learning
A Multimodal Model with Multitask Learning using Convolutional Autoencoder for Clinical Prognosis of Alzheimer’s Disease
MultiResUnet3D implemented by Pytorch
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