Project in het Engels:


Keywords: 3D imaging; machine/deep learning; artificial intelligence; augmented reality; mixed reality; implants; big data; 3D printing

Initiator: Prof. dr. Thomas Maal 

Organisation of initiator(s): Radboud UMC 

Co-initiators & organisation of the co-initiators: Prof. dr. Harrie Weinans (UMC Utrecht), Dr. Peter Seevinck (UMC Utrecht), Dr. Erik Puik (HU University of Applied Sciences Utrecht), Prof. Dr. J Bonjer (AMC/Amsterdam Skills Center), Prof.Dr.Ir. Maarten Steinbuch (Technical University Eindhoven)

Other organizations involved: TU Delft (Prof. dr. Amir Zadpoor), Utrecht Science Park/Fieldlab 3DMedical (Ir. A. de Raad)  

Main research question:

To research and implement an improved way of surgery, using a full 3D Medical Digital workflow with navigated surgery guidance and 3D-printed tooling and implants.


Medical data and images can nowadays be transferred into virtual products to enable personalized digital models that simulate body (parts) and facilitate improved diagnosis, treatment and surgery. In addition, innovations in 3D-printing technology have started the introduction of patient-specific surgical guides and implants in the operating theatre, but the full potential of such digital solutions has not been fully utilized and valorized. The goal of this project is to develop, implement and valorize a 3D-Medical workflow for simulation and completion of an entire surgery, including digital pre-planning, options for augmented reality and navigation guidance, as well as automatic generation of 3D-printed patient-specific surgical tools, drill/saw guides and implants. A database will be built with 3D surgical planning and results, to select the best treatment for a specific patient, using artificial intelligence such as machine/deep learning algorithms.The project will involve a selection of ‘Use Case’ applications that are expected to benefit most from such digital workflow; for example, in trauma, orthopedic, cardio, vascular, brain and plastic surgery, thereby incorporating aspects such as e.g. locomotion, load bearing, blood flow and breathing. Specific tools will be implemented that use MRI and/or CT radiological images as input and a complete operating guideline as output with an immediate workflow for navigation and the design and manufacturing of 3D-printed guiding tools and implants. The consortium will collaborate with industry partners on 3D-printing, game development, augmented reality and big data as well as other stake holders such as surgeon associations, government administrators, hospital management, legal representatives and educational institutes. It will utilize full potential of the medical (imaging) data infrastructure of the hospitals involved. We expect this project to accelerate an advanced way of working that guides surgeons through complex surgery, incorporating advanced navigation and 3D-printed tools and implants in a smart and flexible surgical factory.

For more information, please contact:

Prof. dr. Thomas Maal