Abstract
Radiologic evaluation of images from computed tomography (CT) or magnetic resonance imaging for diagnostic purposes is based on the analysis of single slices, occasionally supplementing this information with 3D reconstructions as well as surface or volume rendered images. However, due to the complexity of anatomical or pathological structures in biomedical imaging, innovative visualization techniques are required to display morphological characteristics three dimensionally. Virtual reality is a modern tool of representing visual data, The observer has the impression of being “inside” a virtual surrounding, which is referred to as immersive imaging. Such techniques are currently being used in technical applications, e.g. in the automobile industry. Our aim is to introduce a workflow realized within one simple program which processes common image stacks from CT, produces 3D volume and surface reconstruction and rendering, and finally includes the data into a virtual reality device equipped with a motion head tracking cave automatic virtual environment system. Such techniques have the potential to augment the possibilities in non-invasive medical imaging, e.g. for surgical planning or educational purposes to add another dimension for advanced understanding of complex anatomical and pathological structures. To this end, the reconstructions are based on advanced mathematical techniques and the corresponding grids which we can export are intended to form the basis for simulations of mathematical models of the pathogenesis of different diseases.
Similar content being viewed by others
Notes
ProMesh is a free software which allows for visualization of unstructured grids in 2D and 3D and also for the improvement of surface and volume grids respectively tetrahedralization
A software standard defines how a format or a language has to be implemented such that each one who is interested in applying it may understand how to use it. The tiff standard defines the byte and bit order of a tiff image which allows the image to be called “tiff”.
A mesh is a set of of basic elements which describe a set. For example, a triangular mesh describes a surface. The surface is constructed by means of triangles. A connected surface hence is constructed by means of single triangles which all have neighbors which also belong to the surface. In particular, the nodes which describe the single triangles (three for each triangle) are shared with neighbor elements, in particular those who are not at an outer boundary (for open surfaces).
References
Community. Osirix software. http://www.osirix-viewer.com/
MITK. Software. http://mitk.org/wiki/MITK
Wössner, U., Aumüller, M., Lang, U.: Driving an active stereo cave with a cluster of pcs. VR-Cluster 03: Workshop on Commodity Clusters for Virtual Reality, IEEE VR, Los Angeles, (2003)
Hoffer, M., Poliwoda, C., Wittum, G.: Visual reflection library: a framework for declarative GUI programming on the Java platform. Comput. Vis. Sci. 16, 181 (2013). https://doi.org/10.1007/s00791-014-0230-y
Rantzau, D., Frank, K., Lang, U., Rainer, D., Wössner, U.: Covise in the cube: An environment for analyzing large and complex simulation data. In: Proceedings of the 2nd workshop on immersive projection technology (IPT 98), Ames, Iowa (1998)
Vogel, A., Reiter, S., Rupp, M., Nägel, A., Wittum, G.: Ug 4: a novel flexible software system for simulating pde based models on high performance computers. Comp. Vis. Sci. 16(4), 165–179 (2013)
Reiter, S., Vogel, A., Heppner, I., Rupp, M., Wittum, G.: A massively parallel geometric multigrid solver on hierarchically distributed grids. Comput. Vis. Sci. 16(4), 151–164 (2013)
http://dicom.nema.org/. Dicom standard. web page, (2011)
Lorensen, William E., Cline, Harvey E.: Marching cubes: a high resolution 3D surface construction algorithm. Comput. Gr. 21(4), 163–169 (1987)
Newman, T.S., Yi, H.: A survey of the marching cubes algorithm. Comput. Gr. 30(5), 854–879 (2006)
Reiter, S.: Effiziente algorithmen und datenstrukturen für die realisierung von adaptiven, hierarchischen gittern auf massiv parallelen systemen. Ph.D. thesis University of Frankfurt (2015)
Reiter, S., Wittum, G.: http://promesh3d.com/ (2017)
International Organization for Standardization. Tiff standard. https://www.iso.org/standard/2181.html (1998)
Wavefront Technologies. Wavefront obj standard. http://www.martinreddy.net/gfx/3d/OBJ.spec (1989)
Brooks, Rodney A.: A quantitative theory of the hounsfield unit and its application to dual energy scanning. J. Comput. Assist. Tomogr. 1(4), 487–493 (1977)
Broser, P.J., Schulte, R., Roth, A., Helmchen, F., Waters, J., Lang, S., Sakmann, B., Wittum, G.: Nonlinear anisotropic diffusion filtering of three-dimensional image data from 2-photon microscopy. J. Biom. Opt. 9(6), 1253–1264 (2004)
Jungblut, D., Queisser, G., Wittum, G.: Inertia based filtering of high resolution images using a GPU cluster. Comput. Vis. Sci. 14, 181–186 (2011)
Otsu, N.: A threshold selection method from gray-level histograms. IEEE Trans. Syst. Man Cybern. 9, 62–66 (1979)
Oracle. Java native interface. http://docs.oracle.com/javase/7/docs/technotes/guides/jni/index.html 1993 (2014)
Vogel, A., Xu, J., Wittum, G.: A generalization of the vertex-centered finite volume scheme to arbitrary high order. Comput. Vis. Sci. 13(5), 221–228 (2010)
Bey, J.: Finite-Volumen- und Mehrgitter-Verfahren für Elliptische Randwertprobleme. B.G. Teubn, Berlin (2003)
Hackbusch, W.: Iterative Solution of Large Sparse Systems of Equations. Springer, Berlin (1993)
ter Romeny, B.M.H.: Computational Imaging and Vision Geometry-Driven Diffusion in Computer Vision. Kluwer Academic Publishers, Dordrecht (1994)
Gonzales, R. C., Woods, R. E.: Digital image processing. Pearson Educ; 00004. ISBN-10: 0133356728 ISBN-13: 978-0133356724 (2017)
Suetens, P.: Fundamentals of medical imaging. Cambridge University Press, Cambridge. 2nd edn ASIN: B00DT608R2 (2009)
Dubois, E.: A projection method to generate anaglyph stereo images. In: Proceedings of IEEE international conference on acoustics speech signal processing, (Salt Lake City, UT), vol. 3, pp. 1661–1664 (2001)
Stefan Vilsmeier. Brainlab munich, germany. https://www.brainlab.com/en (1989)
Acknowledgements
We thank M. Aumüller, HLRS Stutttgart, for excellent and friendly support for the CAVE system installation and upgrade, and J. Pieper, GCSC, and A. Chizhov, Ioffe Physical-Technical Institute, RAS, St. Petersburg, for their support when performing the photos at the CAVE. MMK thanks Elisa Ficarra (Politecnico di Torino) for a stimulating discussion about the subject. The authors acknowledge the Goethe Universität Frankfurt for general support and computational resources and the University Erlangen-Nuremberg as well as the Politecnico di Torino for general support. This work has been supported in part by the “Fondazione Cassa di Risparmio di Torino” (Italy), through the “La Ricerca dei Talenti” (HR Excellence in Research) programme and in major part by the Institute of Radiology of the University Medical Center Erlangen. The Authors wish to express their sincere thanks to the anonymous Referees for their thorough and critical reviews of our work.
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by Alfio Grillo.
Rights and permissions
About this article
Cite this article
Knodel, M.M., Lemke, B., Lampe, M. et al. Virtual reality in advanced medical immersive imaging: a workflow for introducing virtual reality as a supporting tool in medical imaging. Comput. Visual Sci. 18, 203–212 (2018). https://doi.org/10.1007/s00791-018-0292-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00791-018-0292-3