Imaging systems and intelligent biomarkers for brain health
The Brain Image Team develops MRI systems and quantitative imaging methods, then applies them in clinical studies and large imaging datasets to investigate vascular disease, brain aging, and neurodegeneration.
Our projects link scanner and sequence development with quantitative measures of brain structure, blood flow, physiology, and function. We then use computational methods to test these measurements in clinical studies and large datasets.
Imaging systems and quantitative MRI
We develop and adapt MRI technology when existing systems or measurements are not enough. The work may involve hardware and magnet design, pulse sequences, acquisition, reconstruction, calibration, or quantitative analysis. Current projects include Halbach-based ultra-low-field systems and 3 T MRI methods for measuring flow, perfusion, cerebrovascular reactivity, tissue properties, and brain function. The program is not tied to a particular field strength or scanner platform.
Brain physiology, vascular health, and aging
Brain anatomy is only part of the picture. We study blood flow, vascular regulation, tissue health, and functional physiology in stroke, aging, and neurodegeneration.
The work includes quantitative MRI, CT, physiological modelling, and multimodal data. The examples below show cerebral blood flow measured with MRI and the estimation of amyloid burden from structural brain images.
Imaging intelligence at scale
We develop computational methods for reconstruction, image translation, segmentation, brain-age modelling, and multimodal analysis. Each method is built around a scientific or clinical question, then tested on data beyond the original cohort.
We are also interested in agent-guided research workflows that improve code through repeated, measurable experiments. The examples below show Aashka Mohite's MRI and genetics methods pipeline alongside a simple code-improvement loop.
One research program
Systems research creates new measurements. Physiological and clinical studies determine which measurements are useful. Large datasets and computational methods test whether the results hold beyond the original scanner or cohort.
People before programs. We expect careful, well-documented work without treating unnecessary competition or exhaustion as evidence of commitment.