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Non-rigid Deformation Pipeline for Compensation of Superficial Brain Shift
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.
Linköping University, Department of Clinical and Experimental Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Anaesthetics, Operations and Specialty Surgery Center, Department of Neurosurgery.
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.ORCID iD: 0000-0002-0442-3524
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: Medical Image Computing and Computer-Assisted Intervention, MICCAI 2013: 16th International Conference, Nagoya, Japan, September 22-26, 2013, Proceedings, Part II, Springer Berlin/Heidelberg, 2013, 141-148 p.Conference paper, Published paper (Refereed)
Abstract [en]

The correct visualization of anatomical structures is a critical component of neurosurgical navigation systems, to guide the surgeon to the areas of interest as well as to avoid brain damage. A major challenge for neuronavigation systems is the brain shift, or deformation of the exposed brain in comparison to preoperative Magnetic Resonance (MR) image sets. In this work paper, a non-rigid deformation pipeline is proposed for brain shift compensation of preoperative imaging datasets using superficial blood vessels as landmarks. The input was preoperative and intraoperative 3D image sets of superficial vessel centerlines. The intraoperative vessels (obtained using 3 Near-Infrared cameras) were registered and aligned with preoperative Magnetic Resonance Angiography vessel centerlines using manual interaction for the rigid transformation and, for the non-rigid transformation, the non-rigid point set registration method Coherent Point Drift. The rigid registration transforms the intraoperative points from the camera coordinate system to the preoperative MR coordinate system, and the non-rigid registration deals with local transformations in the MR coordinate system. Finally, the generation of a new deformed volume is achieved with the Thin-Plate Spline (TPS) method using as control points the matches in the MR coordinate system found in the previous step. The method was tested in a rabbit brain exposed via craniotomy, where deformations were produced by a balloon inserted into the brain. There was a good correlation between the real state of the brain and the deformed volume obtained using the pipeline. Maximum displacements were approximately 4.0 mm for the exposed brain alone, and 6.7 mm after balloon inflation.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2013. 141-148 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 8150
National Category
Engineering and Technology Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-106901DOI: 10.1007/978-3-642-40763-5_18ISI: 000342835100018ISBN: 978-3-642-40762-8 (print)ISBN: 978-3-642-40763-5 (print)OAI: oai:DiVA.org:liu-106901DiVA: diva2:719342
Conference
16th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2013), Nagoya, Japan, September 22-26, 2013
Available from: 2014-05-23 Created: 2014-05-23 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 (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: 2017-05-02Bibliographically approved

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Maria Marreiros, Filipe MiguelRossitti, SandroWang, ChunliangSmedby, Örjan

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Maria Marreiros, Filipe MiguelRossitti, SandroWang, ChunliangSmedby, Örjan
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Center for Medical Image Science and Visualization (CMIV)Media and Information TechnologyThe Institute of TechnologyDivision of Radiological SciencesFaculty of Health SciencesDepartment of Clinical and Experimental MedicineDepartment of NeurosurgeryDepartment of Radiology in Linköping
Engineering and TechnologyMedical and Health Sciences

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