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ir. V. (Matteo) Janzen

ir. V. (Matteo) Janzen

Researcher/Postdoc
ir. V. (Matteo) Janzen
  • Computational Imaging

Research Programs

Strategic Program Cancer

Biography

Biography

Matteo is an assistant professor investigating adaptive Radiotherapy through automatic segmentation, speeding-up image acquisition/reconstruction and synthesis with the aid of deep learning. 

Background
Matteo is born in Como (Italy) in May 1989 and studied Physics at Insubria University graduating (cum laude) in March 2014. In those years he gained interest in experimental Physics, with a predilection for particle detectors. Following this interest, he had the opportunity to perform profilometry measurements of an anti-proton beam and measure the diameter of the Sun with a pixelated silicon detector and develop a detector for spectral measurements of neutrons produced by an in-hospital linear accelerator.
After getting in touch with the hospital environment and feeling the need of broadening his horizons, he decided to step into the field of medical imaging, where, by chance, detectors are somehow involved. From May 2014 to May 2018 he was enrolled as a PhD candidate at the Radiotherapy Department of the Universitair Medisch Centrum Utrecht (The Netherlands). During his PhD project, he had the luck to discover the beauty of magnetic resonance imaging in the practical realm of radiotherapy.
Until December 2021, Matteo was employed as a post-doc/clinical scientist facilitating the clinical implementation of deep learning methods in the radiotherapy department and ideating/validating approaches for future use, e.g. in the field of data-driven image reconstruction.

In January 2022, Matteo was appointed assistant professor continuing his clinical support, teaching and research activities within the radiotherapy department and Computational Imaging group.

Research Output (41)

Influence of eye movement on lens dose and optic nerve target coverage during craniospinal irradiation

Hoeben Bianca A W, Seravalli Enrica, Wood Amber M L, Bosman Mirjam, Matysiak Witold P, Maduro John H, van Lier Astrid L H M W, Maspero Matteo, Bol Gijsbert H, Janssens Geert O Nov 2021, In: Clinical and translational radiation oncology. 31 , p. 28-33 6 p.

Synthetic CT for single-fraction neoadjuvant partial breast irradiation on an MRI-linac

Groot Koerkamp Maureen L, de Hond Yvonne J M, Maspero Matteo, Kontaxis Charis, Mandija Stefano, Vasmel Jeanine E, Charaghvandi Ramona K, Philippens Marielle E P, van Asselen Bram, van den Bongard H J G Desirée, Hackett Sara S, Houweling Antonetta Christina 24 Mar 2021, In: Physics in medicine and biology. 66

Deep learning-based synthetic-CT generation in radiotherapy and PET:A review

Spadea Maria Francesca, Maspero Matteo, Zaffino Paolo, Seco Joao Mar 2021, In: Medical Physics. 48 , p. 6537-6566 30 p.

Real-time 3D motion estimation from undersampled MRI using multi-resolution neural networks

Terpstra Maarten, Maspero Matteo, Bruijnen T, Verhoeff Joost, Lagendijk JJW, van den Berg CAT 2021, In: Medical Physics. 48 , p. 6597-6613 17 p.

Deep learning-based synthetic CT generation for paediatric brain MR-only photon and proton radiotherapy

Maspero Matteo, Bentvelzen Laura G, Savenije Mark Hf, Guerreiro Filipa, Seravalli Enrica, Janssens Geert O, van den Berg Cornelis At, Philippens Marielle Ep 22 Sep 2020, In: Radiotherapy & Oncology. 153 , p. 197-204 8 p.

Deep learning-based image reconstruction and motion estimation from undersampled radial k-space for real-time MRI-guided radiotherapy

Terpstra Maarten, Maspero Matteo, D'Agata F, Stemkens Bjorn, Intven Martijn, Lagendijk JJW, van den Berg CAT, Tijssen Rob 14 May 2020, In: Physics in Medicine and Biology. 65 , p. 155015 14 p.

Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy.

Savenije Mark, Maspero Matteo, Sikkes Gonda G, van der Voort van Zyp Jochem, Kotte ANTJ, Bol GH, van den Berg CAT 11 May 2020, In: Radiation Oncology. 15 , p. 104 12 p.

Deep learning-based MR-to-CT synthesis:The influence of varying gradient echo-based MR images as input channels

Florkow Mateusz C, Zijlstra Frank, Willemsen Koen, Maspero Matteo, van den Berg Cornelis A T, Kerkmeijer Linda G W, Castelein René M, Weinans Harrie, Viergever Max A, van Stralen Marijn, Seevinck Peter R Apr 2020, In: Magnetic Resonance in Medicine. 83 , p. 1429-1441 13 p.

A single neural network for cone-beam computed tomography-based radiotherapy of head-and-neck, lung and breast cancer

Maspero Matteo, Houweling Antonetta C., Savenije Mark H.F., van Heijst Tristan C.F., Verhoeff Joost J.C., Kotte Alexis N.T.J., van den Berg Cornelis A.T. Apr 2020, In: Physics and Imaging in Radiation Oncology. 14 , p. 24-31 8 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.

All research output

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