Computational Imaging Group

Brief description

Matteo Maspero is an assistant professor and clinical medical physicist-in-training with a focus on adaptive radiotherapy, image acquisition/reconstruction, registration, and segmentation enhanced by deep learning. Since 2023, he has taken a step closer to clinical implementation through formal medical physics training at the Radiotherapy Department of UMC Utrecht. He remains actively involved in translational research, bridging the gap between computational developments and clinical application. Matteo is also affiliated with DLinRT.eu, a European initiative on deep learning in radiotherapy.

Background

Born in Como, Italy, in May 1989, Matteo studied Physics at the University of Insubria, graduating cum laude in March 2014. His early academic interests centered around particle detectors, performing profilometry of an antiproton beam, using silicon detectors to measure the sun’s diameter, and developing a detector for neutron spectral measurements from a hospital linear accelerator.

His transition to medical imaging was both opportunistic and deliberate, drawn by the continued presence of detectors in a clinically relevant field. From May 2014 to May 2018, Matteo completed a PhD in the Radiotherapy Department of UMC Utrecht, where he explored MR-only radiotherapy for prostate cancer and discovered a lasting passion for magnetic resonance imaging within the context of radiotherapy.

Following his PhD, Matteo joined the department as a postdoctoral researcher focused on clinical translation of deep learning techniques for adaptive radiotherapy. He was appointed assistant professor in January 2022. Since 2023, he is training to become a certified clinical medical physicist (radiotherapy), further deepening his integration of clinical and technical expertise.

Projects

Key publications

Huijben EM, Terpstra ML, Pai S, Thummerer A, Koopmans P, Afonso M, van Eijnatten M, Gurney-Champion O, Chen Z, Zhang Y, Zheng K,…, Maspero M. Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report. Medical image analysis. 2024 Oct 1;97:103276. https://doi.org/10.1016/j.media.2024.103276
Spadea MF, Maspero M, Zaffino P, Seco J. Deep learning-based synthetic-CT generation in radiotherapy and PET: a review. Med Phys. 2021 Nov; 48(11); https://doi.org/10.1002/mp.15150, https://arxiv.org/2102.02734.
Maspero M, Savenije MHF, Dinkla AM, Seevinck PR, Intven MPW, Juergenliemk-Schulz IM, Kerkmeijer LGW, Van den Berg CAT. Dose evaluation of fast synthetic-CT generation using a generative adversarial network for general pelvis MR-only radiotherapy. Phys Med Biol, 2018 Aug; 63(18):185001-13 https://doi.org/10.1088/1361-6560/aada6d.
Maspero M, Houweling AC, Savenije MH, van Heijst TC, Verhoeff JJ, Kotte AN, van den Berg CA. A single neural network for cone-beam computed tomography-based radiotherapy of head-and-neck, lung and breast cancer. Physics and Imaging in Radiation Oncology. 2020 Apr; 14:24-31. https://doi.org/10.1016/j.phro.2020.04.002.
Savenije MH & Maspero M, Sikkes GG, van der Voort VZ, TJ KA, Bol GH, T van den Berg CA. Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy. Radiation Oncology. 2020 May; 15(1):104. https://doi.org/10.1186/s13014-020-01528-0.

PhD thesis MR-only Radiotherapy of prostate cancer, 1 May 2014 - 28 April 2018, Utrecht, The Netherlands, ISBN: 978-90-393-6953-1, Utrecht University.

Publications

2025

Wang Y, Lombardo E, Thummerer A, Blöcker T, Fan Y, Zhao Y, Papadopoulou CI, Hurkmans C, Tijssen RH, Görts PA, Tetar SU,…, Maspero M. TrackRAD2025 challenge dataset: Real-time tumor tracking for MRI-guided radiotherapy. arXiv preprint arXiv:2503.19119. 2025 Mar 24. https://doi.org/10.48550/arXiv.2503.19119
Rogowski V, Svalkvist A, Maspero M, Janssen T, Maruccio FC, Gorgisyan J, Scherman J, Häggström I, Wåhlstrand V, Gunnlaugsson A, Nilsson MP. Impact of deep learning model uncertainty on manual corrections to auto-segmentation in prostate cancer radiotherapy. arXiv preprint arXiv:2502.18973. 2025 Feb 26. https://doi.org/10.48550/arXiv.2502.18973
Thummerer A, van der Bijl E, Galapon AJ, Kamp F, Savenije M, Muijs C, Aluwini S, Steenbakkers RJHM, Beuel S, Intven MPW, Langendijk JA, Both S, Corradini S, Rogowski V, Terpstra M, Wahl N, Kurz C, Landry G, Maspero M. SynthRAD2025 Grand Challenge dataset: generating synthetic CTs for radiotherapy. 2025 March. https://doi.org/10.48550/arXiv.2502.17609
Ding M, Maspero M, Littooij AS, van Grotel M, Fajardo RD, van Noesel MM, van den Heuvel-Eibrink MM, Janssens GO. Deep learning-based auto-contouring of organs/structures-at-risk for pediatric upper abdominal radiotherapy. arXiv preprint arXiv:2411.00594. 2025 April. https://doi.org/10.48550/arXiv.2411.00594

2024

Huisman S, Maspero M, Philippens M, Verhoeff J, David S. Validation of SynthSeg segmentation performance on CT using paired MRI from radiotherapy patients. NeuroImage. 2024 Dec 1;303:120922. https://doi.org/10.1016/j.neuroimage.2024.120922
Kolenbrander ID, Prasad V, Zikken L, van Eijnatten MA, Maspero M, Pluim JP. Assessing the Robustness of Image Registration Models Under Domain Shifts with Learnable Input Images. InInternational Workshop on Biomedical Image Registration 2024 Oct 5 (pp. 101-111). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-73480-9_8
Reinders FC, Savenije MH, de Ridder M, Maspero M, Doornaert PA, Terhaard CH, Raaijmakers CP, Zakeri K, Lee NY, Aliotta E, Rangnekar A. Automatic segmentation for magnetic resonance imaging guided individual elective lymph node irradiation in head and neck cancer patients. PhIRO. 2024 Oct 1;32:100655. https://doi.org/10.1016/j.phro.2024.100655
Huijben EM, Terpstra ML, Pai S, Thummerer A, Koopmans P, Afonso M, van Eijnatten M, Gurney-Champion O, Chen Z, Zhang Y, Zheng K,…, Maspero M. Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report. Medical image analysis. 2024 Oct 1;97:103276. https://doi.org/10.1016/j.media.2024.103276
Thummerer A, Zaffino P, Spadea MF, Knopf A, Maspero M. Artificial intelligence to generate synthetic CT for adaptive particle therapy. InImaging in Particle Therapy: Current practice and future trends 2024 Jun 1 (pp. 8-1). Bristol, UK: IOP Publishing. https://iopscience.iop.org/book/edit/978-0-7503-5117-1/chapter/bk978-0-7503-5117-1ch8.epub
Jacobs L, Mandija S, Liu H, van den Berg CA, Sbrizzi A, Maspero M. Generalizable synthetic MRI with physics‐informed convolutional networks. Medi Phys. 2024 May;51(5):3348-59. arXiv:2305.12570
Kolenbrander ID, Maspero M, Hendriksen AA, Pollitt R, van der Voort van Zyp JR, van den Berg CA, Pluim JP, van Eijnatten MA. Deep‐learning‐based joint rigid and deformable contour propagation for magnetic resonance imaging‐guided prostate radiotherapy. Med Phys. 2024 Apr;51(4):2367-77. https://doi.org/10.1002/mp.17000

2023

Thummerer A, Huijben E, Terpstra M, Gurney-Champion OJ, Afonso MV, Pai S, Koopmans P, van Eijnatten M, Perko Z, Maspero M. SynthRAD2023 challenge design: Synthesizing computed tomography for radiotherapy. University Medical Center Utrecht (UMCU); 2023.
Nijskens L, van den Berg CAT, Verhoeff JJC, Maspero M. Investigating contrast generalisation in deep learning-based brain MRI-to-CT synthesis. Physica Medica, 2023 Aug; 112:102642, https://doi.org/10.1016/j.ejmp.2023.102642; arXiv:arXiv.2303.10202; Zenodo:10.5281/zenodo.7742642.
Terpstra M, Maspero M, Verhoeff JJC, van den Berg CAT. Accelerated respiratory-resolved 4D-MRI with separable spatio-temporal neural networks. Med Phys, 2023, arXiv:2211.05678.
Thummerer A, van der Bijl E, Galapon Jr A, Verhoeff JJC, Langendijk JA, Both S, van den Berg CAT, Maspero, M. SynthRAD2023 Grand Challenge dataset: Generating synthetic CT for radiotherapy. Med Phys. 2023 Jul;50(7):4664-4674; https://doi.org/10.1002/mp.16529; arXiv:2303.16320.

2022

Seravalli E, Sierts M, Brand E, Maspero M, David S, Philippens MEP, Voormolen EHJ, Verhoeff JJC. Dosimetric feasibility of direct post-operative MR-Linac-based stereotactic radiosurgery for resection cavities of brain metastases. Radiother Oncol, 2022 Dec; 179:109456; https://doi.org/10.1016/j.radonc.2022.109456.
Terpstra M, Maspero M, Verhoeff JJC, van den Berg CAT. Accelerated respiratory-resolved 4D-MRI with separable spatio-temporal neural networks. Submitted to Medical Physics, 2022 Nov, arXiv:2211.05678.
Jacobs L, Mandija S, Hongyan L, van den Berg CAT, Sbrizzi A, Maspero M. Generalizable synthetic multi-contrast MRI generation using physics-informed convolutional networks. In Proc Intl Soc Mag Reson Med. 2022: 30, 2850; https://archive.ismrm.org/2022/2850.html.
Terpstra ML, Maspero M, Sbrizzi A, van den Berg CAT. ⊥-loss: a symmetric loss function for magnetic resonance imaging reconstruction and image registration with deep learning. Medical Image Analysis. 2022 Aug; 102509; https://doi.org/10.1016/j.media.2022.102509.
Maspero M, Keijnemans K, Hackett SL, Raaymakers BW, Verhoeff JJC,Fast MF, van den Berg CAT. OC-0772 Deep learning-based 4D synthetic CT for lung radiotherapy. ESTRO2022, May 8-12.

2021

Terpstra ML, Maspero M, Bruijnen T, Verhoeff JJC, Lagendijk JJ, van den Berg CA. Real‐time 3D motion estimation from undersampled MRI using multi‐resolution neural networks. Medical Physics. 2021 Nov;48(11):6597-613; https://doi.org/10.1002/mp.15217, code https://gitlab.com/computational-imaging-lab/tempest.
Spadea MF & Maspero M, Zaffino P, Seco J. Deep learning-based synthetic-CT generation in radiotherapy and PET: a review. Med Phys. 2021 Nov; 48(11);https://doi.org/10.1002/mp.15150, https://arxiv.org/2102.02734.
Hoeben BAW, Seravalli E, Wood AML, Bosman M, Matysiak WP, Maduro JH, van Lier ALHMW, Maspero M, Bol GH, Janssens GO. Influence of eye movement on lens dose and optic nerve target coverage during craniospinal irradiation. Clin Transl Radiat Oncol. 2021 Aug; 31:28-33 https://doi.org/10.1016/J.CTRO.2021.08.009.
Koerkamp ML, de Hond YJ, Maspero M, Kontaxis C, Mandija S, Vasmel JE, Charaghvandi RK, Philippens ME, van Asselen B, van den Bongard HD, Hackett SS. Synthetic CT for single-fraction neoadjuvant partial breast irradiation on an MRI-linac. Phys Med Biol. 2021 Mar; https://doi.org/10.1088/1361-6560/abf1ba.

2020

Maspero M, Bentvelzen LG, Savenije MHF, Guerreiro F, Seravalli E, Janssens GOR, van den Berg CAT, Philippens MEP. Deep learning-based synthetic CT generation fo paediatric brain MR-only photon and proton radiotherapy. Radiother Oncol. 2020 Dec; 153:197:204. https://doi.org/10.1016/j.radonc.2020.09.029.
Terpstra ML, Maspero M, D’Agata F, Stemkens B, Intven MP, Lagendijk JJ, Van den Berg CA, Tijssen RH. Deep learning-based image reconstruction and motion estimation from undersampled radial k-space for real-time MRI-guided radiotherapy. Phys Med Biol. 2020 May; 65(15):5015. https://doi.org/10.1088/1361-6560/ab9358.
Savenije MH, Maspero M, Sikkes GG, van der Voort VZ, TJ KA, Bol GH, T van den Berg CA. Clinical implementation of MRI-based organs-at-risk auto-segmentation with convolutional networks for prostate radiotherapy. Radiation Oncology. 2020 May; 15(1):104. https://doi.org/10.1186/s13014-020-01528-0.
Maspero M, Houweling AC, Savenije MH, van Heijst TC, Verhoeff JJ, Kotte AN, van den Berg CA. A single neural network for cone-beam computed tomography-based radiotherapy of head-and-neck, lung and breast cancer. Physics and Imaging in Radiation Oncology. 2020 Apr; 14:24-31. https://doi.org/10.1016/j.phro.2020.04.002.
Florkow MC, Zijlstra F, Willemsen K, Maspero M, van den Berg CAT, Kerkmeijer LGW, Castelein RM, Weinas H, Viergever MA, van Stralen M, Seevinck PR. Deep learning-based MR-to-CT synthesis: the influence of varying gradient echo-based MR images as input channels. Mag Res Med. 2020 Apr; 83(4):1429-41. https://doi.org/10.1002/mrm.28008.
Eppenhof KA, Maspero M, Savenije MH, de Boer JC, van der Voort van Zyp JR, Raaymakers BW, Raaijmakers AJ, Veta M, van den Berg CA, Pluim JP. Fast contour propagation for MR‐guided prostate radiotherapy using convolutional neural networks. Medical Physics. 2020 Mar; 47(3):1238-48. https://doi.org/10.1002/mp.13994.
Meliado EF, Raaijmakers AJE, Sbrizzi A, Steensma BR, Maspero M, Savenije MHF, Luijten PR, van den Berg CAT. A deep learning method for image-based subject-specific local SAR assessment. Mag Res Med. 2020 Feb; 83(2):695-711. https://doi.org/10.1002/mrm.27948.

2019

de Muinck Keizer D, Kerkmeijer LWG, Maspero M, Andreychenko A, van der Voort van Zyp J, van den Berg CAT, Raaymakers B, Lagendijk JJW, de Boer J. Soft-tissue prostate intrafraction motion tracking in 3D cine-MR for MR-guided radiotherapy. Phys Med Biol, 2019 Dec; 64(23):235008. https://doi.org/10.1088/1361-6560/ab5539.
Kurz C, Maspero M, Savenije MHF, Landry G, Kamp F, Li M, Pinto M, Parodi K, Belka C, van den Berg CAT. CBCT correction using a cycle-consistent generative adversarial network and unpaired training to enable photon and proton dose calculation. Phys Med Biol, 2019 Nov; 64(22):225004. https://doi.org/10.1088/1361-6560/ab4d8c.
Dinkla AM, Florkow MC, Maspero M, Savenije MHF, Zijlstra F, Doornaert PAH, van Stralen M, Philippens MEP, van den Berg CAT, Seevinck PR. Dosimetric evaluation of synthetic CT for head and neck radiotherapy generated by a patch-based 3D convolutional neural network. Med Phys, 2019 Sep; 46(9):4095-4104. https://doi.org/10.1002/mp.13663.

2018

Dinkla AM, Wolterink JM, Maspero M, Savenije MHF, Verhoeff JJC, Seravalli E, Išgum I, Seevinck PR, van den Berg CAT. MR-Only Brain Radiation Therapy: Dosimetric Evaluation of Synthetic CTs Generated by a Dilated Convolutional Neural Network. Int J Radiat Oncol Biol Phys, 2018 Nov; 102(4):801-812. 10.1016/j.ijrobp.2018.05.058.
Maspero M, Tyyger M, Tijssen RHN, Seevinck PR, Intven M, van den Berg CAT. Feasibility of magnetic resonance imaging-only rectum radiotherapy with a commercial synthetic-computed tomography generation solution. Phys Imaging Radiat Oncol, 2018 (7):58-64. https://doi.org/10.1016/j.phro.2018.09.002.
Kerkmeijer LGW, Maspero M, Meijer GJ, van der Voort van Zyp JRN, de Boer HCJ, van den Berg CAT. Magnetic Resonance Imaging Only Workflow for Radiotherapy Simulation and Planning in Prostate Cancer. Clin Oncol, 2018; 30(11):692-701. https://doi.org/10.1016/j.clon.2018.08.009.
Maspero M, Savenije MHF, Dinkla AM, Seevinck PR, Intven MPW, Juergenliemk-Schulz IM, Kerkmeijer LGW, Van den Berg CAT. Dose evaluation of fast synthetic-CT generation using a generative adversarial network for general pelvis MR-only radiotherapy. Phys Med Biol, 2018 Aug; 63(18):185001-13 https://doi.org/10.1088/1361-6560/aada6d.
Maspero M, Seevinck PR, Willems NJW, Sikkes GG, de Kogel GJ, de Boer HCJ, van der Voort van Zyp JRN, van den Berg CAT. Evaluation of gold fiducial marker manual localisation for magnetic resonance-only prostate radiotherapy. Radiat Oncol, 2018 Jun; 13(1):105. https://doi.org/10.1186/s13014-018-1029-7 Code available at https://doi.org/10.24433/CO.9de8bf35-71a7-40ed-8470-bf89536a348d

2017

Maspero M, van den Berg CAT, Landry G, Belka C, Parodi K, Seevinck PR, Raaymakers BW, Kurz C. Feasibility of MR-only proton dose calculations for prostate cancer radiotherapy using a commercial pseudo-CT generation method. Phys Med Biol, 2017 Nov; 62(24):9159-9176. https://doi.org/10.1088/1361-6560/aa9677. Code available at https://doi.org/10.24433/CO.763408fd-9964-4fe8-9689-39fe12937930 or https://matteomaspero.github.io/MRonlyProton-pCTwithAir/.
Maspero M, van den Berg CAT, Zijlstra F, Sikkes GG, de Boer HCJ, Meijer GJ, Kerkmeijer LGW, Viergever MA, Lagendijk JJW, Seevinck PR. Evaluation of an automatic MR-based gold fiducial marker localisation method for MR-only prostate radiotherapy. Phys Med Biol, 2017 Oct; 62(20):7981-8002. https://doi.org/10.1088/1361-6560/aa875f.
Andreychenko A, Kroon PS, Maspero M, Jürgenliemk-Schulz I, De Leeuw AA, Lam MG, Lagendijk JJ, van den Berg CA. The feasibility of semi-automatically generated red bone marrow segmentations based on MR-only for patients with gynecologic cancer. Radiother Oncol, 2017 Apr; 123(1):164-168. https://doi.org/10.1016/j.radonc.2017.01.020.
Maspero M, Seevinck PR, Schubert G, Hoesl MA, van Asselen B, Viergever MA, Lagendijk JJ, Meijer GJ, van den Berg CA. Quantification of confounding factors in MRI-based dose calculations as applied to prostate IMRT. Phys Med Biol, 2017 Feb; 62(3):948-965. https://doi.org/10.1088/1361-6560/aa4fe7; Code available at [https://doi.org/10.24433/CO.763408fd-9964-4fe8-9689-39fe12937930] or https://matteomaspero.github.io/pseudo-CT_generation/.

2015

Maspero M, Berra A, Conti V, Giannini G, Ostinelli A, Prest M, et al. A real time scintillating fiber Time of Flight spectrometer for LINAC photoproduced neutrons. Nucl Ins Meth Phys Res A, 2015 Mar; 777:154–60. https://doi.org/10.1016/j.nima.2014.12.101.

2012

Faurobert M, Fang C, Corbard T, Sigismondi C, Raponi A, De Rosi G, Bianda M, Ramelli R, Caccia M, Maspero M, Negrini L, Wang X. Atmospheric fluctuations below 0.1 Hz during drift-scan solar diameter measurements, 2012, EAS Publication Series 55:381-383. https://doi.org/10.1051/eas/1255054.