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Automatic generation of patient specific models for hip surgery simulation
Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology.
2006 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Simulation of surgical procedures in computer based simulator systems is a relatively new area of interest in the field of medical technology. Many different systems are under development, but it is still far until this technique becomes routine in a clinical environment.

One limitation with these systems is that the computer generated models of the anatomy are ususally not patient specific. In general these systems contain one or a couple of generic models, reflecting the normal anatomy. In order to use these systems as tools for preoperative planning, it must be possible to generate computer models from real patient cases. This is relevant also when these systems are used for training and education, since the surgeon can practice on a variety of real cases, ranging from routine procedures to more complex, or more unusual, tasks.

To produce patient specific models a segmentation process is generally involved. A manual segmentation method, where a user delineates the interesting structure slice by slice in a patient dataset, is a very tedious process, and the result tends to vary between different users. The results would be more consistent, and the process would be more time and cost efficient, if a computer performed this task automatically, with a limited amount of user interaction.

This work focus on automatic segmentation of hip bones from computer tomography scans, in order to generate patient specific computer models for a hip fracture surgery simulator. The segmentation is carried out by matching a template dataset to a patient dataset using a method called the morphon method. Each point in the template is categorised as one of three tissue types, soft tissue (background), spongy bone (bone interior), or cortical bone (bone surface). When this dataset has been matched to the patient dataset the information in the template can be projected onto the patient dataset and used to find the different objects in this dataset.

The presented method can be used in other applications as well. One example demonstrated in this thesis is segmentation of a structure in the brain called the hippocampus.

Place, publisher, year, edition, pages
Linköping: Linköpings universitet , 2006. , 49 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1243
Series
LiU-TEK-LIC, 24
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:liu:diva-34135Local ID: 20909ISBN: 91-85523-95-X (print)OAI: oai:DiVA.org:liu-34135DiVA: diva2:254983
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-11-26
List of papers
1. Non-rigid registration using morphons
Open this publication in new window or tab >>Non-rigid registration using morphons
2005 (English)In: Image Analysis: 14th Scandinavian Conference, SCIA 2005, Joensuu, Finland, June 19-22, 2005. Proceedings / [ed] Heikki Kalviainen, Jussi Parkkinen and Arto Kaarna, Springer Berlin/Heidelberg, 2005, Vol. 3540, 501-510 p.Chapter in book (Refereed)
Abstract [en]

The Morphon, a non-rigid registration method is presented and applied to a number of registration applications. The algorithm takes a prototype image (or volume) and morphs it into a target image using an iterative, multi-resolution technique. The deformation process is done in three steps: displacement estimation, deformation field accumulation and deformation. The framework could be described in very general terms, but in this paper we focus on a specific implementation of the Morphon framework. The method can be employed in a wide range of registration tasks, which is shown in four very different registration examples, 2D photographs of hands and faces, 3D CT data of the hip region, and 3D MR brain images.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2005
Series
Lecture Notes in Computer Science, ISSN 0302-9743 (print), 1611-3349 (online) ; 3540
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-48191 (URN)10.1007/11499145_51 (DOI)978-3-540-26320-3 (ISBN)e-978-3-540-31566-7 (ISBN)3-540-26320-9 (ISBN)
Available from: 2009-10-11 Created: 2009-10-11 Last updated: 2013-11-26Bibliographically approved
2. A hip surgery simulator based on patient specific models generated by automatic segmentation
Open this publication in new window or tab >>A hip surgery simulator based on patient specific models generated by automatic segmentation
2006 (English)In: Medicine Meets Virtual Reality 14: Accelerating Change in Healthcare: Next Medical Toolkit / [ed] James D Westwood; et al, Amsterdam, Nederländerna: IOS Press, 2006, 431-436 p.Conference paper, Published paper (Refereed)
Abstract [en]

The use of surgical simulator systems for education and preoperative planning is likely to increase in the future. A natural course of development of these systems is to incorporate patient specific anatomical models. This step requires some kind of segmentation process in which the different anatomical parts are extracted. Anatomical datasets are, however, usually very large and manual processing would be too demanding. Hence, automatic, or semi-automatic, methods to handle this step are required. The framework presented in this paper uses nonrigid registration, based on the morphon method, to automatically segment the hip anatomy and generate models for a hip surgery simulator system.

Place, publisher, year, edition, pages
Amsterdam, Nederländerna: IOS Press, 2006
Series
Studies in Health Technology and Informatics, ISSN 0926-9630 ; 119
Keyword
Surgery simulation, hip, patient specific models, segmentation, registration, morphon
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-32716 (URN)000269690200092 ()18638 (Local ID)978-1-58603-583-9 (ISBN)18638 (Archive number)18638 (OAI)
Conference
Medicine Meets Virtual Reality Conference MMVR06,2006
Available from: 2009-10-09 Created: 2009-10-09 Last updated: 2015-10-08Bibliographically approved
3. Non-rigid registration for automatic fracture segmentation
Open this publication in new window or tab >>Non-rigid registration for automatic fracture segmentation
2006 (English)In: Image Processing, 2006, Atlanta: IEEE , 2006, 1185-1188 p.Conference paper, Published paper (Refereed)
Abstract [en]

Automatic segmentation of anatomical structures is often performed using model-based non-rigid registration methods. These algorithms work well when the images do not contain any large deviations from the normal anatomy. We have previously used such a method to generate patient specific models of hip bones for surgery simulation. The method that was used, the morphon method, registers two-or three-dimensional images using a multi-resolution deformation scheme. A prototype image is iteratively registered to a target image using quadrature filter phase difference to estimate the local displacement. The morphon method has in this work been extended to deal with automatic segmentation of fractured bones. Two features have been added. First, the method is modified such that multiple prototypes (in this case two) can be used. Second, normalised convolution is utilized for the displacement estimation, to guide the registration of the second prototype, based on the result of the registration of the first one

Place, publisher, year, edition, pages
Atlanta: IEEE, 2006
Series
International Conference on Image Processing. Proceedings, ISSN 1522-4880
National Category
Medical and Health Sciences
Identifiers
urn:nbn:se:liu:diva-34136 (URN)10.1109/ICIP.2006.312695 (DOI)000245768500297 ()20910 (Local ID)1-4244-0480-0 (ISBN)e-1-4244-0481-9 (ISBN)20910 (Archive number)20910 (OAI)
Conference
IEEE International Conference on Image Processing (ISIP 2006), 8-11 October 2006, Atlanta, GA, USA
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2015-10-09
4. Automatic segmentation of CT and MR volume data using non-rigid morphon registration
Open this publication in new window or tab >>Automatic segmentation of CT and MR volume data using non-rigid morphon registration
(English)Manuscript (preprint) (Other academic)
Abstract [en]

Automatic segmentation of anatomical structures is often performed using model based non-rigid registration methods. The morphon algorithm is one such method. In this algorithm, two or three dimensional images are registered using a multi-resolution deformation scheme. A prototype image is iteratively registered to a target image, using local phase difference to estimate the displacement between the images. This method has been extended with normalised convolution, to guide the registration process using prior knowledge about the target image. By defining a certainty mask used in the normalised convolution one can either specify a region of interest in the target image, or, on the other hand, occlude regions in the image that should not affect the matching. Two different applications are presented, which each demonstrates the use of this method for automatic segmentation.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-102004 (URN)
Available from: 2013-11-26 Created: 2013-11-26 Last updated: 2014-10-08

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