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dr. A. (Alessandro) Sbrizzi

dr. A. (Alessandro) Sbrizzi

Associate Professor
dr. A. (Alessandro) Sbrizzi
  • Computational Imaging

Biography

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 and NWO-Demonstrator-2018.

Research Output (34)

Fast and accurate modeling of transient-state, gradient-spoiled sequences by recurrent neural networks

Liu Hongyan, van der Heide Oscar, van den Berg Cornelis A T, Sbrizzi Alessandro jul 2021, In: NMR in Biomedicine. 34 , p. 1-18

Accelerated MR-STAT reconstructions using sparse Hessian approximations

van der Heide Oscar, Sbrizzi Alessandro, van den Berg Cornelis A T 22 jun 2020, In: IEEE transactions on medical imaging. 39 , p. 3737-3748 12 p.

Conditional safety margins for less conservative peak local SAR assessment:A probabilistic approach

Meliadò Ettore Flavio, Sbrizzi Alessandro, van den Berg Cornelis A T, Steensma Bart R, Luijten Peter R, Raaijmakers Alexander J E 3 jun 2020, In: Magnetic Resonance in Medicine. 84 , p. 3379-3395 17 p.

High-resolution in vivo MR-STAT using a matrix-free and parallelized reconstruction algorithm

van der Heide Oscar, Sbrizzi Alessandro, Luijten Peter R, van den Berg Cornelis A T 1 apr 2020, In: NMR in Biomedicine. 33 16 p.

A deep learning method for image-based subject-specific local SAR assessment

Meliadò E F, Raaijmakers A J E, Sbrizzi A, Steensma B R, Maspero M, Savenije M H F, Luijten P R, van den Berg C A T 1 feb 2020, In: Magnetic Resonance in Medicine. 83 , p. 695-711 17 p.

MR-MOTUS:model-based non-rigid motion estimation for MR-guided radiotherapy using a reference image and minimal k-space data

Huttinga Niek R F, van den Berg Cornelis A T, Luijten Peter R, Sbrizzi Alessandro 10 jan 2020, In: Physics in medicine and biology. 65 , p. 15004 19 p.

Nonrigid 3D motion estimation at high temporal resolution from prospectively undersampled k-space data using low-rank MR-MOTUS

Huttinga Niek R F, Bruijnen Tom, van den Berg Cornelis A T, Sbrizzi Alessandro 2020, In: Magnetic Resonance in Medicine. 85 , p. 2309-2326 18 p.

Real-time assessment of potential peak local specific absorption rate value without phase monitoring:Trigonometric maximization method for worst-case local specific absorption rate determination

Meliadò Ettore Flavio, Sbrizzi Alessandro, van den Berg Cornelis A T, Luijten Peter R, Raaijmakers Alexander J E 2020, In: Magnetic Resonance in Medicine. 85 , p. 3420-3433 14 p.

MRI‐based transfer function determination through the transfer matrix by jointly fitting the incident and scattered B+1 field

Tokaya Janot P, Raaijmakers Alexander J E, Luijten Peter R, Sbrizzi Alessandro, van den Berg Cornelis A T 21 okt 2019, In: Magnetic Resonance in Medicine. 83 , p. 1081-1095 15 p.

Understanding the Combined Effect of k-Space Undersampling and Transient States Excitation in MR Fingerprinting Reconstructions

Stolk Christiaan C., Sbrizzi Alessandro okt 2019, In: IEEE Transactions on Medical Imaging. 38 , p. 2445-2455

All research output

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