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dr. ir. P.R. Seevinck Associate Professor

  • Image Sciences Institute

P.R. Seevinck

Contact

Research Programs

Biography

Peter Seevinck graduated Biomedical Engineering at the Eindhoven University of Technology in 2005. In 2009, he received his PhD in Medical Imaging at Utrecht University after defending his thesis entitled “Multimodal imaging of holmium-loaded microspheres for internal radiation therapy”.

Currently Peter is appointed Associate Professor (UHD) at the Image Sciences Institute in the Imaging Division of UMC Utrecht. He acts as a coordinator and lecturer in several courses in the field of MRI. His research is focusing on the development and clinical introduction of novel MR imaging methods and advanced machine learning algorithms for minimally invasive and safe personalized image-guided diagnosis and therapy. Examples of these novel approaches include MRI-guided device visualization for cardiac stem cell therapy and brachytherapy, MRI-only radiotherapy treatment planning for more efficient and shorter treatment workup and MRI-based bone imaging (BoneMRI), reducing radiation burden and workflow complexity. He has >50 publications in this field, and has been awarded several (personal) scientific and valorisation grants including VENI (interventional MRI), IMDI ZonMw (MRI-based radiotherapy planning), TTW Take-off phase I and II (commercialization of BoneMRI) and TTW Smart Industry (Deep learning-based image synthesis for orthopedics), NWO KIEM (BoneMRI in the shoulder) and Eurostars (additive manufacturing for orthopedics).

Peter Seevinck is co-founder of MRIguidance B.V., a company that commercializes BoneMRI, the first medical imaging technique that visualizes both bone and soft tissue, without the need for hazardous radiation. BoneMRI renders MRI a one-stop-shop workflow both for diagnostic/prognostic purposes as well as for innovative surgical purposes (e.g. pre-operative planning, navigation, virtual/augmented reality and robotics). For the patient such a one-stop-shop approach could lead to less radiological examinations, less hospital visits and a lower radiation burden.  “With the CE marking of BoneMRI in 2019 an important milestone has been reached, as this opens the door towards widespread usage for the benefit of the patient”.

Research Output (59)

Visualization of gold fiducial markers in the prostate using phase-cycled bSSFP imaging for MRI-only radiotherapy

Shcherbakova Yulia, Bartels Lambertus Wilbert, Mandija Stefano, Beld Ellis, Seevinck Peter R, van der Voort van Zyp Jochem R N, Kerkmeijer Linda G W, Moonen Chrit T W, Lagendijk Jan J W, Van den Berg Cornelis A T 11 sep 2019, In: Physics in Medicine and Biology. 64 , p. 185001 1 p.

Dosimetric evaluation of synthetic CT for head and neck radiotherapy generated by a patch-based three-dimensional convolutional neural network

Dinkla Anna M, Florkow Mateusz C, Maspero Matteo, Savenije Mark H F, Zijlstra Frank, Doornaert Patricia A H, van Stralen Marijn, Philippens Marielle E P, van den Berg Cornelis A T, Seevinck Peter R sep 2019, In: Medical Physics. 46 , p. 4095-4104 10 p.

MRI artifact simulation for clinically relevant MRI sequences for guidance of prostate HDR brachytherapy

Beld Ellis, Moerland Marinus A., van Zyp Jochem R. N. van der Voort, Viergever Max A., Lagendijk Jan J. W., Seevinck Peter R. 26 apr 2019, In: Physics in Medicine and Biology. 64 , p. 095006

Synthetic CT generation for Head and Neck radiotherapy by a 3D convolutional neural network

Dinkla A., Florkow M., Maspero M., Savenije M., Zijlstra F., Doornaert P., Van Stralen M., Philippens M., Seevinck P., Van den Berg N. apr 2019, In: Radiotherapy and Oncology. 133 , p. S268-S269

isoPhasor:a generic and precise marker visualization, localization, and quantification method based on phase saddles in 3D MR imaging

Bouwman Job G, Custers Bram A, Bakker Chris J G, Viergever Max A, Seevinck Peter R mrt 2019, In: Magnetic Resonance in Medicine. 81 , p. 2038-2051 14 p.

CT synthesis from MR images for orthopedic applications in the lower arm using a conditional generative adversarial network

Zijlstra F., Willemsen K., Florkow M. C., Sakkers R. J.B., Weinans H. H., Van Der Wal B. C.H., Van Stralen M., Seevinck P. R. 1 jan 2019,

Development and Testing of a Magnetic Resonance (MR) Conditional Afterloader for Source Tracking in Magnetic Resonance Imaging-Guided High-Dose-Rate (HDR) Brachytherapy

Beld Ellis, Seevinck Peter R, Schuurman Jeroen, Viergever Max A, Lagendijk Jan J W, Moerland Marinus A 15 nov 2018, In: International Journal of Radiation Oncology Biology Physics. 102 , p. 960-968 9 p.

The anterior longitudinal ligament in diffuse idiopathic skeletal hyperostosis: ossified or displaced?

Kuperus Jonneke S., Smit Esther J. M., Pouran Behdad, van Hamersvelt Robbert W., van Stralen Marijn, Seevinck Peter R., Buckens Constantinus F., Bleys Ronald L. A. W., Weinans Harrie H., Oner F. Cumhur, de Jong Pim A., Verlaan Jorrit-Jan sep 2018, In: Journal of Orthopaedic Research. 36 , p. 2491-2496

Dose evaluation of fast synthetic-CT generation using a generative adversarial network for general pelvis MR-only radiotherapy

Maspero M, Savenije MHF, Dinkla AM, Seevinck PR, Intven MPW, Jurgenliemk I, Kerkmeijer LGW, van den Berg CAT 13 aug 2018, In: Physics in Medicine and Biology. 63 , p. 185001 11 p.

Active tracked intramyocardial catheter injections for regenerative therapy with real-time MR guidance:feasibility in the porcine heart

Tseng Cheyenne C S, Wenker Steven, Bakker Maarten H, Kraaijeveld Adriaan O, Dankers Patricia Y W, Seevinck Peter R, Smink Jouke, Kimmel Scott, van Slochteren Frebus J, Chamuleau Steven A J 7 aug 2018, In: EuroIntervention. 15 , p. e336-e339

All Research Output (59)
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