Biomedical Engineering Course Catalogue
Note: The course catalogues, the SGS Calendar, and ACORN list all graduate courses associated with ECE – please note that not all courses will be offered every year.
JEB1433H Medical Imaging
TBA
JEB1444H Neural Engineering
Neural Engineering is an emerging field of research at the crossroads of neuroscience, electrophysiology, signal processing, computer science and nonlinear science. Neural Systems exhibit an amazing variety of instabilities, fluctuations, richness of forms and structures. They can be modeled at the micro and macro levels using parametric and nonparametric methods that are based on differential and integral equations, respectively.
Topics covered in the course include the following: (i) A general perspective of neurobiology and neural engineering. (ii) Parametric neural models described by nonlinear rate processes. (iii) Nonparametric neural models described by the Volterra-Wiener approach. (iv) Neuroglial networks of the brain. Two computer-based projects, dealing with a parametric and a non-parametric neural model, provide hands on experiences to supplement the lectures.
BME1459H Protein Engineering
Protein engineering has advanced significantly with the emergence of new chemical and genetic approaches. These approaches have allowed the modification and recombination of existing proteins to produce novel enzymes with industrial applications and furthermore, they have revealed the mechanisms of protein function. In this course, we will describe the fundamental concepts of engineering proteins with biological applications. A background in molecular biology is recommended. Course topics include: review of the fundamentals of molecular biology, random mutagenesis, site-directed mutagenesis, non-canonical amino acid substitution, DNA recombination, directed evolution and fusion proteins.
BME1466H Advanced Topics on Magnetic Resonance Imaging
This graduate level course is intended to provide an in-depth coverage on the theory, practice, and applications of magnetic resonance imaging (MRI). Applications in cardiovascular and oncological imaging, amongst others, will be investigated, as well as the MR imaging techniques, pulse sequences, and contrast agents appropriate to different applications. The format is based on a combinatorial lecture/literature research approach.
Learning Objectives:
- Understand fundamental physics of nuclear magnetic resonance and magnetic resonance imaging
- Become familiar with the most advanced MRI methods and their applications. These include cardiac MRI, perfusion MRI, metabolic MRI, rapid MRI, and contrast agents/molecular imaging.
- Prepare a comprehensive literature review article on one of the special topics.
HAD5751H AI Development and Implementation in Healthcare
Despite promises that Artificial Intelligence (AI) will transform health care, the development and adoption of AI in health care has lagged behind other industries. Some of the causes for this lag include restrictions on the use of health care data, resistance from the clinical community, the gap between hype and reality of AI, ethical concerns, regulation of health technologies, and difficulties bridging the cultures of healthcare and engineering. Yet despite spectacular failures such as Watson Health, AI is slowly beginning to appear in health care settings, most often in the context of research, but increasingly in the form of FDA and Health Canada-approved products. The aim of this course is to build a critical understanding of end-to-end lifecycle of AI in health care, from working with raw health care data, to integration of AI with clinical workflow, through to regulatory approval. This course will be of particular interest to translational AI researchers looking to apply their work to health care, as well as health care practitioners and informaticians seeking to understand how to leverage AI in their industry.
Full details can be found on the IHPME website.
BME1472H Fundamentals of Neuromodulation Technology and Clinical Applications
As a graduate course offered jointly through BME and ECE, this course teaches the fundamental topics underlying electrical neuromodulation therapy devices. These include the theory of neural excitation predicted by cable theory, principles of neural recording, basics of electrophysiological techniques and hardware, fundamentals of the mammalian nervous system, long-term performance of implanted devices, and advanced techniques for selectively controlling neural activity. The class will also cover selected literature of important scientific or clinical applications in electrical neuromodulation, where each student will present and lead the discussion of each assigned paper(s).