COVID-19 Medical Image Analysis using Machine Learning
The aim of this project is to Investigate Machine Learning (ML) methods for processing biomedical image data, with a particular focus on identifying COVID19-related symptoms to improve early diagnosis.
Working with PhD students from the Oxford Institute of Biomedical Engineering and the Big Data Institute, we will start by getting all project members up to speed in Python and Pytorch, and then work in small groups to develop simple classifiers, likely using CT scans in conjunction with medical metadata, to identify COVID-affected lungs. By the end of Michaelmas we aim to put forward a novel research proposal, likely involving image segmentation and building upon work done with classifiers, on which we will work throughout Hilary. Ultimately we hope to write a short research paper about our findings.
This project is open to anyone interested in machine learning and applying it within biomedical imaging. Some experience with Python is useful but not essential, and no experience with Pytorch is expected - the first half of the project is geared towards learning practical ML within a project setting.
In collaboration with: