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# 6001CEM Project | |
This repository contains the created neural networks for my 6001CEM Final Year Project. | |
The project was conducted to answer the research question: **To what extent can deep learning algorithm based neural networks identify the presence of Alzheimer’s Disease from patient MRI scans?** | |
The dataset used can be found at: **https://www.kaggle.com/datasets/sachinkumar413/alzheimer-mri-dataset** | |
This project involved creating neural networks that would detect the presence of Alzheimer's Disease (AD) from patient MRI scans (binary classification - accuracy score is based on a yes/no answer as to whether the neural network detects the presence of AD) and networks that would detect the severity of AD from a patient's MRI scan, if present (4 class classification - accuracy score is based on the neural network classifying the patient's MRI scans into 1 of 4 distinct categories). | |
## There a total of 6 neural networks (there are technically 3 but were split into 6 - binary and multi-class classification - so they would run faster): | |
- **'TensorFlow4Class'** - Neural network created using TensorFlow, provides an accuracy score for 4 class classification. | |
- **'TensorFlowBinary'** - Neural network created using TensorFlow, provides an accuracy score for binary classification. | |
- **'ResNet4Class'** - Neural network created using PyTorch and a pretrained ResNet model, provides an accuracy score for 4 class classification. | |
- **'ResNetBinary'** - Neural network created using PyTorch and a pretrained ResNet model, provides an accuracy score for binary classification. | |
- **'PyTorchBinary'** - Neural network created using PyTorch, provides an accuracy score for binary classification. | |
- **'PyTorch4Class'** - Neural network created using PyTorch, provides an accuracy score for 4 class classification. | |
## There are 4 datasets present: | |
- **'clean_dataset'** - Used in 'TensorFlow4Class'. This dataset is the original and contains 4 classes ('Non Demented', 'Moderate Demented', 'Mild Demented', 'Very Mild Demented'), obtained from: https://www.kaggle.com/datasets/sachinkumar413/alzheimer-mri-dataset. | |
- **'clean_dataset_binary'** - Used in 'TensorFlowBinary'. Same as the original dataset, except the images are categorised into two folders ('Demented' and 'Non Demented'). | |
- **'clean_dataset_split'** - Used in 'PyTorch4Class' and 'ResNet4Class', same as the original dataset but images are split into 'train' and 'test' folders at a split of 75/25 respectively; the original 4 classes remain. | |
- **'clean_dataset_split_binary'** - Used in 'PyTorchBinary' and 'ResNetBinary', images are categorised into 'train' and 'test' folders at a split of 75/25; images are also categorised into 'Demented' and 'Non Demented' within these folders. |