Brain Imaging and Artificial Intelligence

Theme 2

Development of neuroimaging, computational algorithms/artificial intelligence (AI) to identify biomarkers that can distinguish between healthy and disrupted eye and brain function. 

The game-changing ability to undertake in vivo brain or eye imaging in people with visual disfunction is exploited in Theme 2. Researchers use artificial intelligence (AI) and computational science to probe images of the retina and magnetic resonance imaging/functional magnetic resonance imaging (MRI/fMRI) brain scans to discover retinal and brain “signatures” that represent eye and/or brain diseases. One example is a recent finding that Google’s AI can predict what ophthalmologists cannot: whether a fundus photograph of a human eye belongs to a female or male patient. Our cluster members have expertise in AI, MRIs, and retinal imaging. Additional cluster members have expertise in Alzheimer’s disease, Parkinson’s disease, mood disorders, and cerebral vasculopathies.

Chair

Hee Yeon Im

Principal Investigators

Hye Jin Chung, Silke Cresswell, Deborah Giaschi, Kendall Ho, Hee Yeon Im, Kamyar Keramatian, Geoffrey Law, Da Ma, Ivan Robert Nabi, Ipek Oruç, Helge Rhodin, Claire Sheldon, Miriam Spering

 
Publications and Articles
Publication Journal or Publisher Publication Date
Real-Time Virtual Support as an Emergency Department Strategy for Rural, Remote, and Indigenous Communities in British Columbia: Descriptive Case Study J Med Internet Res
Home Blood Pressure Telemonitoring Technology for Patients With Asymptomatic Elevated Blood Pressure Discharged From the Emergency Department: Pilot Study JMIR Form Res 2024
The Role of Diet in Parkinson’s Disease J Parkinsons Dis
Predicting Four-Year’s Alzheimer’s Disease Onset Using Longitudinal Neurocognitive Tests and MRI Data Using Explainable Deep Convolutional Neural Networks J. Alzheimer's Dis
Poster Session I: Leveraging AI to accelerate scientific discoveries J. Vis
Segmenting Cardiac Ultrasound Videos Using Self-Supervised Learning IEEE Xplore
A graph-based approach can improve keypoint detection of complex poses: a proof-of-concept on injury occurrences in alpine ski racing Sci. Rep.
Eye movements in Parkinson’s disease: from neurophysiological mechanisms to diagnostic tools TINS
Implementing digital emergency medicine: a call to action CJEM
Evidence of factors influencing delays in the diagnosis and treatment of bipolar disorder in adolescents and young adults. Protocol for a systematic scoping review PLoS One

Vision: Molecules, Behaviour, Society Research Excellence Cluster

Eye Care Centre (VGH) 2550 Willow Street
Vancouver, BC Canada V5Z 3N9
Website vision.ubc.ca

Research Excellence Clusters at UBC Vancouver is a joint initiative of the Provost and Vice-President, Academic, UBC Vancouver and the Vice-President, Research and Innovation. Funding support for the clusters is provided by Academic Excellence Funds – UBC Vancouver.

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