Profile photo Alessandro Sbrizzi

Alessandro Sbrizzi

Associate Professor

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
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
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
Time-Resolved Reconstruction of Motion, Force, and Stiffness Using Spectro-Dynamic MRI Max H.C.van Riel, Tristan van Leeuwen, Cornelis A.T.van den Berg, Alessandro Sbrizzi
IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 2023, vol. 9, p.917-927
Static Future Technologies, Dynamic Professionalism  Susan van Hees, Jordi P.D. Kleinloog, Alessandro Sbrizzi, Wouter P.C. Boon
Postdigital Science and Education, 2023, vol. 6, p.135-153