liu.seSearch for publications in DiVA
Change search
ReferencesLink to record
Permanent link

Direct link
Single-Monitor-Mirror Stereoscopic Display
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology.
Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, The Institute of Technology. Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Center for Diagnostics, Department of Radiology in Linköping.ORCID iD: 0000-0002-7750-1917
2013 (English)In: Journal of Graphics Tools, ISSN 2165-347X, Vol. 17, no 3, 85-97 p.Article in journal (Refereed) Published
Abstract [en]

A new single-monitor-mirror stereoscopic display is presented. The stereoscopic display system is composed of one monitor and one acrylic first-surface mirror. The mirror reflects one image for one of the eyes. The geometrical transformations to compute correctly the stereo pair are derived and presented. System considerations such as mirror placement and implications are also discussed.

In contrast to other similar solutions that use fixed configurations, we try to optimize the display area by controlling the mirror placement. Consequently, one of the images needs to be skewed. Advantages of the system include absence of ghosting and flickering.

We also developed the rendering engine for direct volume rendering (DVR) of volumetric datasets mostly for medical imaging visualization and using OpenGL for polygonal datasets and stereoscopic digital photography. The skewing process in this case is integrated into the ray-casting of DVR. Using geometrical transformations, we can compute precisely the directions of the rays, producing accurate stereo pairs. A similar operation is also performed using OpenGL.

Place, publisher, year, edition, pages
Taylor & Francis, 2013. Vol. 17, no 3, 85-97 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-120584DOI: 10.1080/2165347X.2015.1028690OAI: oai:DiVA.org:liu-120584DiVA: diva2:846645
Projects
arior
Funder
Swedish Childhood Cancer Foundation, MT2013-0036Swedish Foundation for Strategic Research VINNOVAVårdal Foundation
Available from: 2015-08-17 Created: 2015-08-17 Last updated: 2016-09-15Bibliographically approved
In thesis
1. Guidance and Visualization for Brain Tumor Surgery
Open this publication in new window or tab >>Guidance and Visualization for Brain Tumor Surgery
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Image guidance and visualization play an important role in modern surgery to help surgeons perform their surgical procedures. Here, the focus is on neurosurgery applications, in particular brain tumor surgery where a craniotomy (opening of the skull) is performed to access directly the brain region to be treated. In this type of surgery, once the skull is opened the brain can change its shape, and this deformation is known as brain shift. Moreover, the boundaries of many types of tumors are difficult to identify by the naked eye from healthy tissue. The main goal of this work was to study and develop image guidance and visualization methods for tumor surgery in order to overcome the problems faced in this type of surgery.

Due to brain shift the magnetic resonance dataset acquired before the operation (preoperatively) no longer corresponds to the anatomy of the patient during the operation (intraoperatively). For this reason, in this work methods were studied and developed to compensate for this deformation. To guide the deformation methods, information of the superficial vessel centerlines of the brain was used. A method for accurate (approximately 1 mm) reconstruction of the vessel centerlines using a multiview camera system was developed. It uses geometrical constraints, relaxation labeling, thin plate spline filtering and finally mean shift to find the correct correspondences between the camera images.

A complete non-rigid deformation pipeline was initially proposed and evaluated with an animal model. From these experiments it was observed that although the traditional non-rigid registration methods (in our case coherent point drift) were able to produce satisfactory vessel correspondences between preoperative and intraoperative vessels, in some specific areas the results were suboptimal. For this reason a new method was proposed that combined the coherent point drift and thin plate spline semilandmarks. This combination resulted in an accurate (below 1 mm) non-rigid registration method, evaluated with simulated data where artificial deformations were performed.

Besides the non-rigid registration methods, a new rigid registration method to obtain the rigid transformation between the magnetic resonance dataset and the neuronavigation coordinate systems was also developed.

Once the rigid transformation and the vessel correspondences are known, the thin plate spline can be used to perform the brain shift deformation. To do so, we have used two approaches: a direct and an indirect. With the direct approach, an image is created that represents the deformed data, and with the indirect approach, a new volume is first constructed and only after that can the deformed image be created. A comparison of these two approaches, implemented for the graphics processing units, in terms of performance and image quality, was performed. The indirect method was superior in terms of performance if the sampling along the ray is high, in comparison to the voxel grid, while the direct was superior otherwise. The image quality analysis seemed to indicate that the direct method is superior.

Furthermore, visualization studies were performed to understand how different rendering methods and parameters influence the perception of the spatial position of enclosed objects (typical situation of a tumor enclosed in the brain). To test these methods a new single-monitor-mirror stereoscopic display was constructed. Using this display, stereo images simulating a tumor inside the brain were presented to the users with two rendering methods (illustrative rendering and simple alpha blending) and different levels of opacity. For the simple alpha blending method an optimal opacity level was found, while for the illustrative rendering method all the opacity levels used seemed to perform similarly.

In conclusion, this work developed and evaluated 3D reconstruction, registration (rigid and non-rigid) and deformation methods with the purpose of minimizing the brain shift problem. Stereoscopic perception of the spatial position of enclosed objects was also studied using different rendering methods and parameter values.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2016. 70 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1762
National Category
Medical Image Processing Radiology, Nuclear Medicine and Medical Imaging Surgery Computer Engineering
Identifiers
urn:nbn:se:liu:diva-130791 (URN)10.3384/diss.diva-130791 (DOI)9789176857724 (Print) (ISBN)
Public defence
2016-09-30, Hugo Theorellsallen (norra entrén), Campus US, Linköping, 09:00 (English)
Opponent
Supervisors
Funder
Swedish Foundation for Strategic Research Knowledge FoundationVINNOVAVårdal Foundation, 2009/0079Swedish Childhood Cancer Foundation, MT2013-0036
Available from: 2016-08-24 Created: 2016-08-24 Last updated: 2016-09-09Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full text

Search in DiVA

By author/editor
Maria Marreiros, Filipe MiguelSmedby, Örjan
By organisation
Center for Medical Image Science and Visualization (CMIV)Media and Information TechnologyThe Institute of TechnologyDivision of Radiological SciencesFaculty of Health SciencesDepartment of Radiology in Linköping
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

Altmetric score

Total: 166 hits
ReferencesLink to record
Permanent link

Direct link