Artikel
Concept for the application of novel intraoperative imaging techniques employing augmented reality visualisation for improved image-guided surgery
Konzept für die Anwendung von neuartigen intraoperativen Bildgebungsmethoden in Verbindung mit augmentierter Realität
Suche in Medline nach
Autoren
-
Martin Oelschlägel
- Universitätsklinikum Carl Gustav Carus, Klinisches Sensoring und Monitoring, Dresden, Deutschland
-
Juliane Müller
- Universitätsklinikum Carl Gustav Carus, Klinisches Sensoring und Monitoring, Dresden, Deutschland
-
Christian Schnabel
- Universitätsklinikum Carl Gustav Carus, Klinisches Sensoring und Monitoring, Dresden, Deutschland
-
Jan Müller
- Technische Universität Dresden, Professur für Grundlagen der Elektrotechnik, Dresden, Deutschland
-
Nico Hoffmann
- Technische Universität Dresden, Professur für Computergraphik und Visualisierung, Dresden, Deutschland
-
NIshant Kumar
- Technische Universität Dresden, Professur für Computergraphik und Visualisierung, Dresden, Deutschland
-
Ute Morgenstern
- Technische Universität Dresden, Institut für Biomedizinische Technik, Dresden, Deutschland
-
Stephan B. Sobottka
- Universitätsklinikum Carl Gustav Carus, Klinik und Poliklinik für Neurochirurgie, Dresden, Deutschland
-
Gabriele Schackert
- Universitätsklinikum Carl Gustav Carus, Klinik und Poliklinik für Neurochirurgie, Dresden, Deutschland
-
Edmund Koch
- Universitätsklinikum Carl Gustav Carus, Klinisches Sensoring und Monitoring, Dresden, Deutschland
-
Gerald Steiner
- Universitätsklinikum Carl Gustav Carus, Klinisches Sensoring und Monitoring, Dresden, Deutschland
-
Matthias Kirsch
- Asklepios Kliniken Schildautal Seesen, Abteilung für Neurochirurgie, Seesen, Deutschland; Universitätsklinikum Carl Gustav Carus, Klinik und Poliklinik für Neurochirurgie, Dresden, Deutschland
| Veröffentlicht: | 8. Mai 2019 |
|---|
Gliederung
Text
Objective: Image-guided interventions, that are based on preoperative acquired data registered to the intraoperative scene using the neuronavigation system, are the gold standard for guidance during resection of pathological tissue. The drawbacks of this approach are the use of preoperatively acquired imaging data and the visualization on different devices and screens which forces the surgeon to match and transfer the presented information by his own to the actual surgical field. To overcome those limitations, we developed a concept that includes the use of information from new intraoperative imaging techniques in connection with 2D/3D image fusion and augmented reality (AR) visualization.
Methods: Intraoperative Thermal Imaging and Intraoperative Optical Imaging are innovative imaging techniques that can be utilized to create two-dimensional cortical maps of information that is currently intraoperatively not provided by imaging modalities (e. g. functional maps, local cortical perfusion state, tumor infiltration zones or tissue histology). In addition, novel imaging techniques that provide high resolution morphological and morpho-chemical imaging data for tissue classification such as Hyperspectral Imaging, Raman Mapping and CARS-Imaging will be incorporated into our concept. The information provided by these methods is based on the intraoperative scene and therefore highly accurate.
Results: The spatially highly resolved two-dimensional maps are calculated from the acquired imaging data of the modalities and co-registered to the three-dimensional reconstructed brain surface (preoperative MRI) of the patient. The heterogenous set of multimodal imaging data is visualized in augmented reality (e.g. with AR glasses or through the microscope). The raw imaging data is enriched by extracted neurotopological as well as neurophysiological information from the different modalities that are most meaningful for the current state of intervention and the actual decision-making process of the surgeon.
Conclusion: Our concept includes the integration of the aforementioned imaging and improved intraoperative decision-making by
- 1.
- co-registered data acquisition,
- 2.
- image processing with 2D/3D image/information fusion, and
- 3.
- augmented reality visualization.
