Biosketch
Aswathi is a PhD student at the Institute for Artificial Intelligence in Medicine and the Institute of Diagnostic and Interventional Radiology at the Technical University of Munich, Germany. She obtained her Bachelor’s in Electronics and Communication Engineering from the University of Kerala, India. She pursued her Master’s in Control and Robotics: Signal and Image Processing at Ecole Centrale de Nantes, France. Her research interests lie in the domain of geometric deep-learning techniques for medical applications. Currently, she is working on deep learning for analysis of brain MRI.
relAI Research
Deep Learning for Longitudinal MR Image Analysis in Multiple Sclerosis Patients
This thesis investigates the application of deep learning-based image analysis techniques to improve the longitudinal assessment of Multiple Sclerosis (MS) using brain MRI scans. The research aims to develop strategies for extracting meaningful information from longitudinal MR scans and integrating them with graph-based modelling approaches to gain deeper insights into the disease progression and predict patient outcomes. The current project involves developing data representation techniques for brain lesions using deep learning models such as CNNs and ViTs, to enhance the accuracy and robustness of the analysis. Example work:
[1] Self-pruning Graph Neural Network for Predicting Inflammatory Disease Activity in Multiple Sclerosis from Brain MR Images
DOI: https://doi.org/10.1007/978-3-031-43993-3_22