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Medical Augmented Reality Facial Data Collection

posted on 22.11.2019, 09:38 by Jan Egger, Christina Gsaxner, Jürgen Wallner
Medical augmented reality (AR) is an increasingly important topic in many medical fields. It enables an x-ray vision to see through real world objects. In surgery, this offers a pre-, intra- or postoperative visualization of “hidden” structures. In example, a surgeon can look through AR glasses directly at a patient while directly visualizing a pathology and the surrounding anatomical structures beforehand. In contrast to a classical monitor view, this provides an overlaid visualization not only on but also in relation to the patient. However, research and development of medical AR-based applications is challenging, because of the unique patient-specific anatomy and pathology. Furthermore, working with patients during the development for weeks or even months is not feasible. One alternative are commercial standard patient phantoms, which are very expensive. Hence, this collection provides a unique and accessible data set of patient-specific head PET-CT scans with corresponding 3D models, provided as stereolitography (STL) files. The STL models are optimized for effective 3D printing at a very low cost. All patients have different facial anatomies and pathologies, enabling the development and evaluation of medical AR applications for head and neck surgery.

The data can be viewd with Studierfenster: www.studierfenster.at

Please use the following citations if you use the data in your work:

J. Egger, C. Gsaxner, J. Wallner. Medical Augmented Reality Facial Data Collection. Figshare, 2019.

C. Gsaxner, A. Pepe, J. Wallner, D. Schmalstieg, J. Egger. Markerless Image-to-Face Registration for Untethered Augmented Reality in Head and Neck Surgery. MICCAI, pp. 236-244, 2019.

C. Gsaxner, J. Wallner, X. Chen, W. Zemann, J. Egger. Facial model collection for medical augmented reality in oncologic cranio-maxillofacial surgery. Scientific Data 6(1):310, 2019.


FWF KLI 678-B31 (enFaced)

COMET K-Project 871132 (CAMed)

TU Graz Lead Project (Mechanics, Modeling and Simulation of Aortic Dissection)

Priv.-Doz. Dr. Dr. Jan Egger was supported as visiting Professor by the Overseas Visiting Scholars Program from the Shanghai Jiao Tong University (SJTU) in China.