You are here

Radiology

Project Leader(s): 

Postdoctoral fellow: Dr. Ian Jeffrey, Electrical and Computer Engineering, University of Manitoba Lead faculty member: Dr. Joe LoVetri, Electrical and Computer Engineering, University of Manitoba

Non-academic participants: 

Among the core components of Magnetic Resonance Imaging (MRI) systems are the radio frequency (RF) transmitter and receiver coils responsible for acquiring the signals used to create images. Specialized imaging techniques typically include the use of custom RF coils to maximize signal-to-noise ratio and localize the area within the body being imaged. The design of such RF coils requires sophisticated electromagnetic (EM) algorithms that include, for example, the modeling of interface circuitry and cabling used to drive the coils.

Project Leader(s): 

Postdoctoral fellow: Dr. Ilker Hacihaliloglu, Department of Orthopaedics, University of British Columbia

Lead faculty member: Dr. David Wilson, Department of Orthopaedics, University of British Columbia

The Canadian National Trauma Registry have recorded that out of 109,738 major injuries occurring in 1999, 4531 had a pelvis fracture. Traditional intraoperative imaging modality in orthopaedic surgery is 2D fluoroscopy which makes identification of 3D bone surfaces very difficult and exposes the patient and the surgical team to harmful ionizing radiation. Ultrasound has traditionally been used to image the body's soft tissue, organs, and blood flow in real time.

Project Leader(s): 

Postdoctoral fellow: Dr. Xiteng Liu, Mathematics and Statistics, York University

Lead faculty member: Dr. Hongmei Zhu, Mathematics and Statistics, York University

Non-academic participants: 

Magnetic Resonance Imaging (MRI) is an important medical imaging technology for clinical diagnostics. However, its slowness in data acquisition poses major problems in practice. In recent years, many research efforts to accelerate MRI data acquisition were based on the compressed sensing (CS) theory. CS is effective for signals that have highly sparse representations. However, it suffers from high computational complexity and lack of performance stability.

Project Leader(s): 

Dr. Adrian Nachman , University of Toronto

Project team: 
Dr. Michael L. G. Joy , (University of Toronto)
Dr. Dawn Jorgenson , (Phillips Medical System, Dept. Heartstream)
Non-academic participants: 
Funding period: 
April 1, 2021 - March 31, 2021
Tags: 
Project Leader(s): 

Dr. Jiri Patera, Université de Montréal

Project team: 
Dr. F. Lesage, École Polytechnique de Montréal
Dr. Hongmei Zhu, York University
Funding period: 
October 1, 2021 - March 31, 2021

The development of new biomedical imaging techniques has resulted in significantly better tools for doctors and scientists to image humans and animals in-vivo. Technological developments and new types of imagers with more capabilities are revolutionizing the field. Currently, available technologies for brain imaging include Magnetic Resonance Imaging (MRI), functional MRI, Diffuse Optical Tomography (DOT), Electro-Encephalography (EEG) and Magneto-Encephalography.

Tags: