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enFaced 2.0 - Instant AR Tool for Maxillofacial Surgery

enFaced 2.0 - Instant AR Tool for Maxillofacial Surgery

Jan Egger (ORCID: 0000-0002-5225-1982)
  • Grant DOI 10.55776/KLI1044
  • Funding program Clinical Research
  • Status ongoing
  • Start April 1, 2022
  • End March 31, 2026
  • Funding amount € 399,588
  • Project website
  • E-mail

Disciplines

Clinical Medicine (90%); Environmental Engineering, Applied Geosciences (10%)

Keywords

    Maxillofacial Surgery, Bone Defect Reconstruction, Navigation, Augmented and Virtual Reality

Abstract

The facial skull is anatomically very complex, due to multiple important anatomical structures and cavities located in an area with very limited space. This makes maxillofacial surgery highly challenging. Computer-aided methods aim on making such surgical interventions more precise and safer, for example, by using patient-specific virtual planning, or intra-operative surgical navigation. However, mapping between computer-generated information, displayed on 2D monitors, and the real anatomical situation within the patient is still mentally very challenging for the surgeon. In this context, augmented reality (AR) can aid by merging 3D virtual medical data directly with the patient in the physical space, for example, through 3D smart glasses, smartphones or tablets. In this interdisciplinary project between computer science and medicine, we develop and investigate an AR tool for surgical visualization and navigation in maxillofacial surgery, to make trauma surgeries more precise, safer, and faster, while keeping the mental demand for the surgeon low. The project builds upon the predecessor project enFaced from 2018, during which the need for such an AR tool has been identified. Now, we will further develop our first prototypes and bring them to most recent hardware, such as the AR smart glass HoloLens 2. In a close collaboration with surgeons who perform maxillofacial trauma surgery on a daily basis, the advantages and disadvantages of our AR tool will be evaluated in detail, and its usability in a real clinical setting will be scientifically assessed. This interdisciplinary research project will be carried out by the Graz University of Technology in cooperation with the Medical University of Graz.

Research institution(s)
  • Technische Universität Graz - 50%
  • Medizinische Universität Graz - 50%
Project participants
  • Jürgen Wallner, Medizinische Universität Graz , associated research partner
International project participants
  • Xiaojun Chen, Shanghai Jiao Tong University - China
  • Nassir Navab, TU München - Germany

Research Output

  • 71 Citations
  • 14 Publications
Publications
  • 2024
    Title GAN-based generation of realistic 3D volumetric data: A systematic review and taxonomy
    DOI 10.1016/j.media.2024.103100
    Type Journal Article
    Author Ferreira A
    Journal Medical Image Analysis
    Pages 103100
    Link Publication
  • 2024
    Title Rethinking realities: A call for accurate terminology in eXtended Reality studies
    DOI 10.1016/j.resplu.2024.100558
    Type Journal Article
    Author Fijacko N
    Journal Resuscitation Plus
    Pages 100558
    Link Publication
  • 2022
    Title Open-Source Skull Reconstruction with MONAI
    DOI 10.48550/arxiv.2211.14051
    Type Preprint
    Author Li J
  • 2023
    Title Why does my medical AI look at pictures of birds? Exploring the efficacy of transfer learning across domain boundaries
    DOI 10.48550/arxiv.2306.17555
    Type Preprint
    Author Jonske F
  • 2023
    Title k-strip: A novel segmentation algorithm in k-space for the application of skull stripping
    DOI 10.1016/j.cmpb.2023.107912
    Type Journal Article
    Author Rempe M
    Journal Computer Methods and Programs in Biomedicine
    Pages 107912
    Link Publication
  • 2022
    Title Back to the Roots: Reconstructing Large and Complex Cranial Defects using an Image-based Statistical Shape Model
    DOI 10.48550/arxiv.2204.05703
    Type Preprint
    Author Li J
  • 2023
    Title Apple Vision Pro for Healthcare: "The Ultimate Display"? -- Entering the Wonderland of Precision Medicine
    DOI 10.48550/arxiv.2308.04313
    Type Preprint
    Author Egger J
  • 2023
    Title Improvement in Disease Diagnosis in Computed Tomography Images by Correlating Organ Volumes with Disease Occurrences in Humans
    DOI 10.3390/biomedinformatics3030036
    Type Journal Article
    Author Van Meegdenburg T
    Journal BioMedInformatics
    Pages 526-542
    Link Publication
  • 2023
    Title Sparse convolutional neural network for high-resolution skull shape completion and shape super-resolution
    DOI 10.1038/s41598-023-47437-6
    Type Journal Article
    Author Li J
    Journal Scientific Reports
    Pages 20229
    Link Publication
  • 2023
    Title Augmented Reality-Guided Apicoectomy Based on Maxillofacial CBCT Scans
    DOI 10.3390/diagnostics13193037
    Type Journal Article
    Author Remschmidt B
    Journal Diagnostics
    Pages 3037
    Link Publication
  • 2023
    Title Open-source skull reconstruction with MONAI
    DOI 10.1016/j.softx.2023.101432
    Type Journal Article
    Author Li J
    Journal SoftwareX
    Pages 101432
    Link Publication
  • 2022
    Title FakeNews: GAN-based generation of realistic 3D volumetric data -- A systematic review and taxonomy
    DOI 10.48550/arxiv.2207.01390
    Type Preprint
    Author Ferreira A
  • 2022
    Title Radiomics in Head and Neck Cancer Outcome Predictions
    DOI 10.3390/diagnostics12112733
    Type Journal Article
    Author Gonçalves M
    Journal Diagnostics
    Pages 2733
    Link Publication
  • 2022
    Title k-strip: A novel segmentation algorithm in k-space for the application of skull stripping
    DOI 10.48550/arxiv.2205.09706
    Type Preprint
    Author Rempe M

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