Bilkent CS 464 Machine Learning
Project Proposal
Group X
Group Members: …
Title: MLRI - MRI Classification via Transfer Learning
Description of The Dataset
The dataset can be accessed on Kaggle under the name Alzheimer Preprocessed Dataset [1]. The
data consists of 6400 preprocessed MRI images of size 128x128 with a total of 4 classes. These
classes are the levels of dementia: mild demented, moderate demented, non-demented, and very
mild demented. The class distribution is imbalanced. For example, for the moderate demented class,
there are 64 images which are 1% of the images. This might require extra steps such as data
augmentation.
The Problem
The main intention behind the project is to make use of MRI data such that it will be able to
automate the Alzheimer classification process, which in return, will significantly reduce the MRI
inspection time of a health professional. While it won't replace doctoral consultation, it will be a
useful tool for doctors during patient consultation. It will work as a second opinion for doctors. The
purpose of the project is to provide assistance to doctors and patients for MRI analysis.
The Planned Milestone
We plan to use PyTorch as the machine learning framework. We will experiment on several pretrained models. EfficientNetv2 architecture will be prioritized during the experiments since it is a
recent state-of-art architecture for image classification tasks with 97.5% top-5 accuracy on the
ImageNet dataset [2]. We plan to pass the data through data augmentation layers and will
experiment with different architectures to replace the top of the neural network. These architectures
will include some different regularization techniques such as dropout. We will also experiment with
different weight initialization techniques and optimizers. Since this is a computationally expensive
task, we plan to use a GPU to train the neural network.
References
[1] S. Kumar and S. Shastri, “Alzheimer MRI preprocessed dataset,” Kaggle, 27-Mar-2022. [Online].
Available: https://www.kaggle.com/datasets/sachinkumar413/alzheimer-mri-dataset. [Accessed:
17-Oct-2022].
[2] “Keras applications,” Keras. [Online]. Available: https://keras.io/api/applications/. [Accessed:
17-Oct-2022].