This project is based on my Master’s thesis under the supervision of Prof. Tommy Kaplan (Computer Science) and Prof. Aviv Mezer (Neuroscience). The research investigates microstructural changes in the brain during aging using statistical methods and machine learning algorithms applied to quantitative MRI (qMRI) data. The project includes data analysis, machine learning, and statistical methods to explore brain region convergence and variability across different age groups.
- qMRI Data Processing: Preprocess quantitative MRI data from multiple brain regions.
- Machine Learning: Apply algorithms like XGBoost and t-SNE for pattern recognition and age group classification.
- Statistical Analysis: Perform advanced statistical tests to assess brain region correlations and variability.
- Visualization: Generate visualizations such as clustering plots and correlation heatmaps.