Collaborate with us
Are you interested in collaborating with Concordia University of Edmonton on the exciting projects we have in the works?
Take a look at these opportunities to see if they’re a good fit for your business, and contact us today!
CT Scan Enhancement opportunity
Diagnostic medical imaging is the largest contributor of artificial radiation exposure in the general population. The health system in North America follows the As Low As Reasonably Achievable (ALARA) principle with regard to radiation exposure; that is, to operate at levels as low as reasonably achievable. Unfortunately, the general tendency is to expose the patients to high level of radiation to obtain good quality CT scan images. Therefore, there is a need for advanced technologies that can enhance CT scan images without exposing the patients to high level of radiation.
Mr. Ed Boraas at Concordia University of Edmonton has developed a machine learning based algorithm that transforms low quality images obtained at low radiation exposure to high quality images. The algorithm has the capability to learn from a patient’s images and thus can potentially reduce the number of scans required over time. This program has been trained using 1500 chest CT scans. Further studies to train the algorithm using a robust data set are planned.
1. CT scanner manufacturers
2. Medical software developers and distributors
This technology can:
1. Potentially enhance low quality CT scan images
2. Be incorporated as a plug-in to existing infrastructure and clinical workflow for CT scanning in hospitals and clinics
3. Potentially improve workflow efficiency in hospitals by reducing the occurrence of follow-up scanning and lowering levels of radiation dose
For more information on this collaboration opportunity, please contact:
Manager, BMO Centre for Innovation and Applied Research
Concordia University of Edmonton