Nils Daniel Forkert

Canada Research Chair in Medical Image Analysis

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


Coming to Canada From

Stanford University, United States

Research involves

Developing advanced processing methods and algorithms for analyzing medical images.

Research relevance

This research will increase our understanding of diseases by applying advanced image analysis algorithms to support diagnosis and treatment decisions.

Advanced Analysis of Medical Images to Promote Personalized Medicine

Neurological and cerebrovascular diseases are a considerable burden for patients and their families. They also cost the Canadian economy billions of dollars every year.

Medical imaging is one of the tools used to conduct medical and neuroscience research in both healthy patients and those who have neurological or cerebrovascular disorders. But advances in medical imaging devices, such as computerized tomography and magnetic resonance imaging, have resulted in an increasing number of multidimensional images that need to be preprocessed, quantitatively analyzed, and visualized.

Dr. Nils Daniel Forkert, Canada Research Chair in Medical Image Analysis, is developing new methods and processes to analyze medical images that will provide a better understanding and knowledge of cerebrovascular and neurological diseases than current standard image analysis tools do.

The idea behind medical image analysis is to create and apply new mathematical techniques and computational algorithms to extract and visualize clinically relevant, quantitative information from an ever-increasing mass of medical imaging data. That information is then used in combination with other information (such as genetic, behavioral and epidemiological data) to generate new knowledge about diseases and to support diagnoses.

Forkert and his research team hope that by developing new algorithms and innovative image analysis software, they will advance our understanding of neurological and cerebrovascular diseases. Ultimately, their research will also support better clinical diagnosis and treatment decisions, and promote precision personalized medicine.