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Sci Data. 2019 Dec 9;6(1):310. doi: 10.1038/s41597-019-0327-8.

Facial model collection for medical augmented reality in oncologic cranio-maxillofacial surgery.

Gsaxner C1,2,3, Wallner J4,5, Chen X6, Zemann W1, Egger J1,2,3,6.

Author information

1
Department of Oral and Maxillofacial Surgery, Medical University of Graz, Auenbruggerplatz 6/1, 8036, Graz, Austria.
2
Computer Algorithms for Medicine Laboratory, Graz, Austria.
3
Institute for Computer Graphics and Vision, Graz University of Technology, Inffeldgasse 16c/II, 8010, Graz, Austria.
4
Department of Oral and Maxillofacial Surgery, Medical University of Graz, Auenbruggerplatz 6/1, 8036, Graz, Austria. j.wallner@medunigraz.at.
5
Computer Algorithms for Medicine Laboratory, Graz, Austria. j.wallner@medunigraz.at.
6
Shanghai Jiao Tong University, School of Mechanical Engineering, 800 Dong Chuan Road, Shanghai, 200240, China.

Abstract

Medical augmented reality (AR) is an increasingly important topic in many medical fields. AR enables x-ray vision to see through real world objects. In medicine, this offers pre-, intra- or post-interventional visualization of "hidden" structures. In contrast to a classical monitor view, AR applications provide visualization not only on but also in relation to the patient. However, research and development of medical AR applications is challenging, because of unique patient-specific anatomies and pathologies. Working with several patients during the development for weeks or even months is not feasible. One alternative are commercial patient phantoms, which are very expensive. Hence, this data set provides a unique collection of head and neck cancer patient PET-CT scans with corresponding 3D models, provided as stereolitography (STL) files. The 3D models are optimized for effective 3D printing at low cost. This data can be used in the development and evaluation of AR applications for head and neck surgery.

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