Diagnostic Classification of Alzheimer’s Disease using an Ensemble of CNNs

This repository contains the group project developed at KTH within the Deep Learning in Data Science course by:

• Anna Fernandez-Rajal
• Carolin Danker
• Ilona Toikka
• Manuel Fraile

This work received the maximum possible grade, an A.

Aim of this work

The goal of this work is to develop an algorithm that classifies images in order to detect Alzheimer's Disease in patients using Convolutional Neural Networks. This project is inspired by:

[1] Islam, J., & Zhang, Y. (2018). Brain MRI analysis for Alzheimer’s disease diagnosis using an ensemble system of deep convolutional neural networks. Brain informatics, 5(2), 1-14.

[2] Yamanakkanavar, N., Choi, J. Y., & Lee, B. (2020). MRI segmentation and classification of human brain using deep learning for diagnosis of alzheimer’s disease: a survey. Sensors, 20(11), 3243.

[3] Marcus DS, Wang TH, Parker J, Csernansky JG, Morris JC, Buckner RL (2007) Open access series of imaging studies (OASIS): cross-sectional MRI data in young, middle aged, nondemented, and demented older adults. J Cogn Neurosci 19(9):1498–1507

[4] http://adni.loni.usc.edu (23.04.2021)

Setup

Datasets are all zipped. Remember tu unzip them in THE SAME FOLDER (/datasets)

Install:

git clone https://github.com/Manu-Fraile/Alzheimer-Classification-CNN.git