Technology and Tools for Quantitative Neurodiagnostics Using Ultra-High Resolution Magnetic Resonance Imaging

The project aims to translate developments in ultra-sensitive MRI sensors to a clinically-relevant setting. To create high-sensitivity sensors for better images, we aim to create a tight-fitting system which places the sensorsâakin to antennasâcloser to the brain. This will improve the quality of the signals that we can extract from the brain, and allow us to use these improvements to capture images that have higher resolution and better contrast. Using this imaging improvement, we aim to then create a large normative dataset of grey matter thicknesses. This dataset will tell us what is ânormalâ for thickness in every part of the brain, and let us capture differences accurately and sensitivity. Ultimately, we aim to become sensitive to even subtle changes in grey matter loss, which may permit us to detect certain neurodegenerative diseases earlier, allowing us to treat them better.

Faculty Supervisor:

Reza Farivar-Mohseni

Student:

William Mathieu

Partner:

Siemens Healthcare Ltd.

Discipline:

Engineering - mechanical

Sector:

Medical devices

University:

Program: