I'm a Research Scientist at Elekta where I work on new technologies to deliver radiotherapy to cancer patients as safely as possible. Previously, I was a software developer/researcher working at the Montreal Neurological Institute.
I'm very interested in deep learning, and organized a Deep Learning for Human Brain Mapping course for the Organization for Human Brain Mapping to teach neuroscientists how deep learning can work for them. I really like visualizations, and some of my brainart can be found in the in the brains section.
Parametric models of EEG power spectra can be used to design digital filters that select different components of the neural signal. Hypotheses based on these models can be validated using time-domain deep learning decoding experiments.
My master's project with Tal Arbel's Probabilistic Vision Group. We cluster features of lesions in MRI to predict future disease activity, and whether patients are likely to be responders to one of the drugs from the clinical trial.
Obtaining accurate white/gray matter segmentations is difficult because the brain's myelin is still growing. Accurate longitudinal segmentations can be used to characterize brain development.
This project uses CNNs to automatically predict whether scans will pass quality control and be useful for follow-up study.
In CBRAIN I worked mainly on implementing the RESTful API and describing it in the OpenAPI specification, as well as created the user registration system.
© Andrew Doyle 2020