Profile photo Alessandro Sbrizzi

Alessandro Sbrizzi

Associate Professor

Strategic program(s):

Biography

Alessandro Sbrizzi is an associate professor at the Computational Imaging group of the UMC Utrecht. He graduated in Mathematics at the Utrecht University and obtained his PhD in 2013 with a thesis focused on modelling and numerical optimization of MRI acquisition & reconstruction processes.

His research focuses on fast multi-parametric MRI (in particular MR-STAT), real-time motion-estimation (MR-MOTUS technique), dynamic systems identification (Spectro-Dynamic MRI), radiofrequency pulse design and the application of machine learning in MRI.

As a Principal investigator, he is a recipient of the following research grants: NWO-VIDI(2021), NWO-VENI(2016), NWO-OpenTech(2021), NWO-HTSM(2020), Netherlands eScience Open(2023), Hanarth Fonds(2023) and NWO-Demonstrator(2018).

See also this video: https://www.youtube.com/watch?v=6LzR6TScybg

Research groups

Cardiovascular imaging and image guided treatment

Research aim

By developing and implementing advanced imaging and AI, we aim to enhance individualized detection, prediction, and minimally invasive treatment of cardiovascular disease.This optimizes patient selection, treatment guidance, and clinical outcomes.
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Computational Imaging Group for MRI Therapy & Diagnostics

Research aim

The Computational Imaging Group develops and apply new MR image acquisition, reconstruction and processing techniques for MRI-guided radiotherapy and diagnostic applications. The group is headed by Prof. Nico van den Berg and dr. Alessandro Sbrizzi.
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Recent publications

High SNR full brain relaxometry at 7T by accelerated MR-STAT Edwin Versteeg, Hongyan Liu, Oscar van der Heide, Miha Fuderer, Cornelis A T van den Berg, Alessandro Sbrizzi
Magnetic Resonance in Medicine, 2024, vol. 92, p.226-235
Water diffusion and T2 quantification in transient-state MRI Miha Fuderer, Oscar van der Heide, Hongyan Liu, Cornelis A T van den Berg, Alessandro Sbrizzi
NMR in Biomedicine, 2024, vol. 37
Towards retrospective motion correction and reconstruction for clinical 3D brain MRI protocols with a reference contrast Gabrio Rizzuti, Tim Schakel, Niek R.F. Huttinga, Jan Willem Dankbaar, Tristan van Leeuwen, Alessandro Sbrizzi
Magnetic Resonance Materials in Physics, Biology and Medicine, 2024, vol. 37, p.807-823
GPU-accelerated Bloch simulations and MR-STAT reconstructions using the Julia programming language Oscar van der Heide, Cornelis A T van den Berg, Alessandro Sbrizzi
Magnetic Resonance in Medicine, 2024, vol. 92, p.618-630
Fast and silent MRI using nonlinear gradient fields at the ultrasonic gradient switching frequency of 20 kHz with a Point Spread Function framework reconstruction Michael J B McGrory, Edwin Versteeg, Alessandro Sbrizzi, Cornelis A T van den Berg, Dennis Klomp, Jeroen C W Siero
Magnetic Resonance in Medicine, 2024, vol. 92, p.2734-2748
Generalizable synthetic MRI with physics-informed convolutional networks Luuk Jacobs, Stefano Mandija, Hongyan Liu, Cornelis A T van den Berg, Alessandro Sbrizzi, Matteo Maspero
Medical Physics, 2023, vol. 51, p.3348-3359