Justin Wan

Canada Research Chair in Scientific Computing

Tier 2 - 2017-11-01
University of Waterloo
Natural Sciences and Engineering Research Council

519-888-4567 ext. 4468

Research involves

Developing sophisticated computational algorithms to advance computer simulation technology for the scientific and health-care sectors.

Research relevance

The research is aimed at improving simulation techniques in computer-aided surgery and enhancing results in medical imaging diagnostics in order to lead to better patient outcomes and savings to the health-care systems.

Visualizing the Ailing Brain and Body

Every year thousands of Canadians develop brain disease and injuries. While we have much better treatments these days, an alarming number of people still die from them. New three-dimensional computer visualization models hold great promise to change this.

Scientific simulation and visualization have come to play increasingly important roles in scientific and engineering discoveries, as well as in clinical applications such as medical imaging diagnosis, medical training, pre-operative planning, and surgical aids. Not only do they help scientists understand the basic biology of disease and damage to the body, but they also help assess treatments, and make individualized predictions and therapy plans. The result: better patient outcomes, lower mortality rates, and lowered overall cost to our health-care system.

As Canada Research Chair in Scientific Computing, Dr. Justin Wan works on new mathematical models and advanced numerical algorithms that can be used in scientific simulations. Combining ideas and theories from mathematical modelling, numerical computation, and optimization, Wan is coming up with remarkable techniques that can simulate various medical conditions such as traumatic brain injury, hydrocephalus (excess fluid in the brain), and cancer. Physicians can then use these simulations to help their patients.

A related focus of Wan's research program is the development of better methods for analyzing medical images to help in diagnoses. The issue of "matching up" multiple images to form a coherent diagnostic picture is particularly important in computer-aided surgery, in which precisely localizing different tissues is critical. Wan is devising a type of computational framework that is aimed at registering "noisy" images of tissues while they are subject to various kinds of motion (such as shrinkage and expansion).