Dr. Javad Alirezaie
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Dr. Javad Alirezaie received his B.Sc. degree in Electrical and Electronic
Engineering from Tehran University in 1988
and his M.A.Sc. and Ph.D. degrees in Systems Design Engineering from University of Waterloo in 1993 and 1996,
respectively. From 1997 to 2000 he was a postdoctoral fellow, an Assistant
Professor and an R&D fellow in a private sector. He joined Ryerson University in 2001. He is currently
an Associate Professor in the Department
of Electrical Engineering and an adjunct professor with the Department of Systems Design Engineering at
My research
interests:
Medical Image Processing:
I am ollaborating with clinician-scientists at the Hospital for Sick
Children (HSC), a leading research institute in pediatric research in
Pattern Recognition:
This research is concerned with providing computers with a perceptual capability in the sense that the significant underlying patterns in a given data set are to be automatically classified or recognized. Data analysis is approached as a problem in determining the similarity between an unknown input pattern and known classes represented in memory. My interest in pattern recognition is currently focused on Magnetic Resonance Images (MRI), mainly segmentation of MR brain images. Traditional and Neural Network approaches are being developed. Pattern recognition has other applications including data analysis, character recognition and classification, remote sensing, etc.
Image Processing:
My interest in image processing is focused on image compression, image segmentation and image enhancement. New methods for image compression, vector quantization and transform coding are investigated including adaptive and neural network approaches. Applications include document processing and medical image archival and retrieval systems.
Myoelectric Signal Decomposition:
Myoelectric signal decomposition resolves a composite signal into its constituent motor unit action potentials (MUAPs). Studying individual MUAPs can provide valuable morphological and temporal information regarding a muscle and its nerve, which can be used in the diagnosis of neuromuscular disorders and in the study of neuromuscular control mechanisms Signal decomposition involves the application and development of pattern recognition techniques and associated signal processing and machine intelligence algorithms
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Publications
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Teaching at Ryerson University
ELE532
: Signals and Systems
ELE888 : Applied
Artificial Inteligence
EE8201 : Computer Vision
EE8202 : Digital
Image Processing
Teaching at
Lakehead University
ENG3556 :
Signals and Systems I
ENG4556 : Signals and
Systems II
ENG2634 : Electronics I
ENG0532 : Digital Signal
Processing
Teaching at Wilfrid
Laurier University
PC319
: Digital Systems Design
CP464 : Selected
Topics in Computer Hardware
CP316 :
Microprocessor II
CP464 : Machine
Vision
Teaching Assistant
at the University of Waterloo (91-96)
SY
DE 192 : Digital Systems
SY DE 292 :
Circuits, Instrumentation, and Measurements
SY DE 352 :
Introduction to Control Systems
SY DE 444 :
Biomedical Engineering: Human Function and its Measurement
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Maintained by javad(at)ryerson.ca |
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