Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Peter Koopmans

Sir Henry Wellcome Postdoctoral Fellow

I develop DTI methods with high spatial resolution. These would allow imaging of white matter fibres in difficult areas, for example where bundles are in close proximity of one another or when they enter grey matter.

One of the main difficulties of high-resolution imaging simply is time and if time is money, the currency of MRI experiments is SNR (signal-to-noise ratio). The better the SNR, the higher the quality of the data and the more reliable the result. SNR scales with the sampled volume and because high-resolution experiments aim to obtain signal from small pieces of tissue, SNR is reduced. This can be compensated by using longer measurement times thereby reducing the impact of noise. However, if we divide the brain up into smaller and smaller units, the absolute number of units to measure increases dramatically which means we already need more time to measure all of them.

My work focuses on tackling the SNR/time issue by developing accelerated acquisition methods that reduce scan times. I use FMRIB’s recently acquired 7 Tesla MRI scanner that is beneficial in two ways: the ultra-high magnetic field boosts the intrinsic SNR of experiments while it independently improves the performance of acceleration methods.

I am funded on a Sir Henry Wellcome postdoctoral fellowship to develop and apply my methods in the brain and spinal cord in the context of chronic pain and motor neuron disease (MND/ALS).

Recent publications

More publications