Background
Maarten Terpstra completed his Bachelors and Masters of Science at the University of Groningen (the Netherlands) in Computing Science in 2010-2016. During his Master he gained an interest in computer vision and visualization, which introduced him to deep learning. After briefly working at the Royal Netherlands Meteorological Institute as software developer, he found the opportunity to further develop his interest in deep learning at the radiotherapy department of the UMC Utrecht, which also introduced him to the magic of MRI.

Maarten obtained his PhD in November, 2023 under the supervision Matteo Maspero, Nico van den Berg and Jan Lagendijk and is currently a Post-doctoral researcher in Computational Imaging Group. Currently, Maarten works on the development of deep learning models for real-time MRI imaging for radiotherapy, including, but not limited to, abdominal and cardiac motion-resolved image reconstruction.

PhD thesis
Real-time MRI-guided radiotherapy with deep learning, 14 November 2023, Utrecht, The Netherlands, ISBN: 978-90-393-7589-1, Utrecht University.

Awards

• NWO Open Mind 2024: ‘Beyond the pixel: Intestinal MRI using neural implicit representations’

Projects

• Subject motion in MRI
• Deep learning in radiotherapy

Most recent publications

• Thomas E. Olausson, Maarten L. Terpstra, Niek R. F. Huttinga, Casper Beijst, Niels Blanken, Teresa Correia, Dominika Suchá, Birgitta K. Velthuis, Cornelis A. T. Berg, and Alessandro Sbrizzi. Free-Running Time-Resolved First-Pass Myocardial Perfusion Using a Multi-Scale Dynamics Decomposition: CMR-MOTUS. arXiv, 2024.
• Evi M.C. Huijben, Maarten L. Terpstra, Arthur Jr. Galapon, Suraj Pai, Adrian Thummerer, Peter Koopmans, Manya Afonso, Maureen Eijnatten, Oliver Gurney-Champion, Zeli Chen, Yiwen Zhang, Kaiyi Zheng, Chuanpu Li, Haowen Pang, Chuyang Ye, Runqi Wang, Tao Song, Fuxin Fan, Jingna Qiu, Yixing Huang, Juhyung Ha, Jong Sung Park, Alexandra Alain-Beaudoin, Silvain Bériault, Pengxin Yu, Hongbin Guo, Zhanyao Huang, Gengwan Li, Xueru Zhang, Yubo Fan, Han Liu, Bowen Xin, Aaron Nicolson, Lujia Zhong, Zhiwei Deng, Gustav Müller-Franzes, Firas Khader, Xia Li, Ye Zhang, Cédric Hémon, Valentin Boussot, Zhihao Zhang, Long Wang, Lu Bai, Shaobin Wang, Derk Mus, Bram Kooiman, Chelsea A.H. Sargeant, Edward G.A. Henderson, Satoshi Kondo, Satoshi Kasai, Reza Karimzadeh, Bulat Ibragimov, Thomas Helfer, Jessica Dafflon, Zijie Chen, Enpei Wang, Zoltan Perko, and Matteo Maspero. Generating synthetic computed tomography for radiotherapy: SynthRAD2023 challenge report. Medical Image Analysis, 2024.
• Maarten Lennart Terpstra. Real-time MRI-guided radiotherapy with deep learning. Utrecht University Library, 2023.

Keywords: Deep learning | Motion estimation/correction | (non)-Cartesian image reconstruction | MR-guided radiotherapy

Social media and other resources
Email: m.l.terpstra-5@umcutrecht.nl | ORCiD | Google Scholar | ResearchGate | LinkedIn