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
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.
The Inverse Problem Accounting for Therapeutic Variability: Development of a Practical Strategy to Maximally Extract Information from Limited Clinical Data
Postdoctoral fellow: Dr. Olivier Barrière, Faculty of Pharmacy, Université de Montréal
Lead faculty member: Dr. Fahima Nekka, Faculty of Pharmacy, Université de Montréal
Pharmacometrics (PM) is an emerging research area defined as “the science that interprets and describes pharmacology in a quantitative fashion to aid efficient drug development and/or regulatory decision”. Over the years, Dr. Nekka’s team has encompassed deep thinking on how to join and enhance emerging worldwide efforts to make mathematical modeling and simulation a complementary language to the usual empirical and clinical methods used in drug discovery and development. This work is part of these sustained efforts to deal with the complex relationship of dose-exposure-effect of drugs.
Fast Feature Extraction and Non Iterative Multi Modal Image Registration for Orthopaedic Trauma using Local Phase Features
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.
Developing a Mathematical Model for Coherent Anti-Stokes Raman Scattering Imaging of Biological Processes in Living Cells
Postdoctoral fellow: Dr. Konstantin Popov, Physics, University of Ottawa
Lead faculty member: Dr. Lora Ramunno, Physics, University of Ottawa
Coherent Anti-Stokes Raman Scattering (CARS) microscopy is a very promising method of directly imaging biological processes occurring in living cells. It is unique because the imaging does not harm the cell, is molecule specific, and does not require the introduction of additional chemicals that may alter the biology. For example, CARS would allow us to visualize how viruses invade a cell membrane, which is still a mystery.
Postdoctoral fellow: Dr. Yijun Lou, Mathematics and Statistics, York University
Lead faculty member: Dr. Jane Heffernan, Mathematics and Statistics, York University
Genital herpes (GH), caused by Herpes simplex virus type 1 or 2 (HSV-1 or -2), is one of the most prevalent sexually transmitted diseases in the world. Currently, there is no effective treatment for GH, but a new vaccine Simplirix (by GSK), is currently in clinical trials. Simplirix has had some success in preventing disease, but only in females that are HSV-1 and -2 negative. Since oral herpes (OH, also caused by HSV-1 and -2) infection can occur at very early ages, vaccination against GH may be most effective in a childhood vaccination program.
Postdoctoral fellow: Dr. Raluca Eftimie, Pathology and Molecular Medicine, McMaster University
Lead faculty member: Dr. Jonathan Bramson, Pathology and Molecular Medicine, McMaster University
Cancer emergence and progression are highly complex processes characterized by interactions among a large variety of cells and signalling molecules. It is very difficult to explain these complex interactions through linear thinking and molecular reductionist approaches. Mathematical modeling is a powerful tool that can substantially enhance our capacity for interpreting the data and generate new hypotheses.
Postdoctoral fellow: Dr. Paul Nguyen, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto
Lead faculty member: Dr. Patrick Brown, Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto
This project aims to develop methods and software for performing spatio-temporal analysis of cancer incidence and smoking data in Ontario over long time periods with high spatial resolution. This will allow changes of cancer incidence over time to be better understood, and accommodate rare cancers that require long study periods in order to accumulate data. Because of small counts common to small area analysis, computationally intensive Bayesian inference methods will be needed.
Several New Mathematical Models for the Integrated Optimization and Control of Human-Friendly Parallel Robots for Advanced Healthcare and Biomedical Manipulation
Postdoctoral fellow: Dr. Zhen Gao, Mechanical Engineering, University of Ontario Institute of Technology
Lead faculty member: Dr. Dan Zhang, Mechanical Engineering, University of Ontario Institute of Technology
This research develops a comprehensive methodology for the integrated optimization and control of human-friendly robotic technology that will be applied for the advanced healthcare and biomedical manipulation. Some original ideas, methods and algorithms are proposed in this research based on several novel mathematical models, which will benefit the development of general robotics in the direction of safety with high performance to human beings.
Postdoctoral fellow: Dr. Majid Jaberi-Douraki, Mathematics and Statistics, York University
Lead faculty member: Dr. Seyed Moghadas, Mathematics and Statistics, York University
A major pharmaceutical intervention for management of many infectious diseases is the use of antiviral drugs. However, the rise of drug resistance poses significant threats to the effectiveness of drugs. This research proposes to determine optimal treatment strategies, through the development of population dynamical models for disease transmission and control, which can minimize the effect of resistance emergence in the population. This work will primarily focus on influenza infection, which still inflicts substantial morbidity, mortality, and socioeconomic costs worldwide.
Modelling Growth Charts with Measurement Error: A Modern Perspective of Prediction of Abnormal Growth Responses in Young Children and Adults
Postdoctoral fellow: Dr. Taraneh Abarin, Public Health Sciences, University of Toronto
Lead faculty member: Dr. Laurent Briollais, Public Health Sciences, University of Toronto
Using modern statistical measurement error methodologies and analysis, we aim to efficiently and accurately discover and characterize predictive models of responses associated with abnormal growth development in young children and adults. This proposal is unique in scope and vision by addressing health issues that threaten the sustainability of the health care system.