SCMR Series of Hands-on Workshops on Machine Learning
Over the past few years, machine learning has shown great potential across the field of medical imaging. It has been demonstrated in overcoming some of the challenges associated with acquisition and reconstruction of imaging data, it has been used to automate the post-processing and analysis of images, as well as improving diagnosis and outcome predictions. ML has potential benefits in Congenital Heart Disease (CHD), including discovery of new clinical markers, more precise classification of CHD phenotypes, as well as predicting disease progression, optimising treatment plans and interventions. However, currently there are relatively few demonstrations of the use of machine learning techniques focussed in CHD. This is in-part due to the significant anatomical heterogeneity found in CHD and the limited amount of data available for training.
This series of workshops is particularly aimed at beginners in the field of Machine Learning. It is particularly suitable for clinicians working in MRI for CHD, but is available to anyone who wants to learn the basics of ML and get first-time hands-on experience in the use of ML in MRI. You will learn:
- Basics of Machine Learning: what is supervised learning, what is a convolution, what is a loss function, what is a batch, what is an epoc
- Understanding how and what data is needed to train a ML network
- How to store data
- How to clean data
- How to label data/create training/test/validation data sets
- How to construct a model
- How to assess the resulting network accuracy
- How to improve a models accuracy
- What can go wrong/what to be aware of
In each workshop we will present slides and code/results - these will all be stored on this github repository, for access before/during/after the workshops. We will encourage you to run on your own laptops during the sessions. All code will be simple to run and you be guided thoroughly. Everything will be run in google colab, and so no specialist computing is required (just a google account).
The goal of these workshops is for you to learn about ML, and take these lessons away and to start collecting good quality data at your own institutions, training your own ML networks, and contributing to registries.
There were four hands-on workshops (July-October 2022). The recordins from each can be found in the corresponding folder above (along with code and slides):
Workshop 1. General principles and theory of machine learning
Workshop 2. A recap plus Part 1 of a classification task in CHD
Workshop 3. Part 2 of a classification task in CHD and recap
Workshop 4. A segmentation task in CHD
This series of workshops has been organised by the SCMR, Machine Learning subcommittee of the Peds/Congenital section. There is no requirement that you are a member of SCMR to attend this event. The event is open to anyone with an interest in ML, specifically focussed on the use MRI in CHD. You do not need any prior experience in coding, although some understanding of python would be beneficial. That there will be some python code involved, however you will still take the key learning objectives away from the sessions, even if you do not understand all of the syntax of the code!