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Evaluation of osseointegration using image analysis and visualization of 2D and 3D image data

Sarve, Hamid (2011). Evaluation of osseointegration using image analysis and visualization of 2D and 3D image data. Diss. (sammanfattning/summary) Uppsala : Sveriges lantbruksuniv., Acta Universitatis agriculturae Sueciae, 1652-6880 ; 2011:61
ISBN 978-91-576-7605-4
[Doctoral thesis]

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PDF (Thesis Summary)
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PDF (Paper VIII in the thesis, Cuanto: A Tool for Quantification of Bone Tissue in the Proximity of Implants)
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[img] Video (Flash) (Flythrough animation, mentioned in Chapter 3.4.5.)
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[img] Video (Flash) (Flythrough animation, mentioned in Chapter 3.4.5.)
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[img] Video (Flash) (Flythrough animation, mentioned in Chapter 3.4.5.)
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[img] Video (Flash) (Flythrough animation, mentioned in Chapter 3.4.5.)
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[img] Video (Flash) (Flythrough animation, mentioned in Chapter 3.4.5.)
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[img] Video (Flash) (Flythrough animation of a sample retrieved from a human, mentioned in Paper VII)
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[img] Video (Flash) (Flythrough animation of a sample retrieved from a human, mentioned in Paper VII)
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Abstract

Computerized image analysis, the discipline of using computers to automatically extract information from digital images, is a powerful tool for automating time consuming analysis tasks. In this thesis, image analysis and visualization methods are developed to facilitate the evaluation of osseointegration, i.e., the biological integration of a load-carrying implant in living bone.

Adequate osseointegration is essential in patients who are in need of implant treatment. New implant types, with variations in bulk material and surface structural parameters, are continuously being developed. The main goal is to improve and speed up the osseointegration and thereby enhance patient well-being. The level of osseointegration can be evaluated by quantifying the bone tissue in proximity to the implant in e.g., light microscopy images of thin cross sections of bone implant samples extracted from humans or animals. This operator dependent quantitative analysis is cumbersome, time consuming and subjective. Furthermore, the thin sections represent only a small region of the whole sample.

In this thesis work, computerized image analysis methods are developed to automate the quantification step. An image segmentation method is proposed for classifying the pixels of the images as bone tissue, non-bone tissue or implant. Subsequently, bone area and bone implant contact length in regions of interest are quantified. To achieve an accurate classification, the segmentation is based on both intensity and spatial information of the pixels. The automated method speeds up and facilitates the evaluation of osseointegration in the research laboratories.

Another aim of this thesis is extending the 2D analysis to 3D and presenting methods for visualization of the 3D image volumes. To get a complete picture, information from the whole sample should be considered, rather than thin sections only. As a first step, 3D imaging of the implant samples is evaluated. 3D analysis methods, which follow the helix shaped implant thread and collects quantified features along the path, are presented. Additionally, methods for finding the position of the 2D section in the corresponding 3D image volume, i.e., image registration, are presented, enabling a direct comparison of the data from the two modalities. These novel and unique 3D quantification and visualization methods support the biomaterial researchers with improved tools for gaining a wider insight into the osseointegration process, with the ultimate goal of improved quality of life for the patients.

Authors/Creators:Sarve, Hamid
Title:Evaluation of osseointegration using image analysis and visualization of 2D and 3D image data
Series/Journal:Acta Universitatis agriculturae Sueciae (1652-6880)
Year of publishing :24 August 2011
Volume:2011:61
Number of Pages:93
Papers/manuscripts:
NumberReferences
1Hamid Sarve, Joakim Lindblad, Carina B. Johansson, Gunilla Borgefors and Victoria F. Stenport (2007). Quantification of Bone Remodeling in the Proximity of Implants. In Proceedings of the 12th International Conference on Computer Analysis of Images and Patterns (CAIP), Vienna, Austria, Lecture Notes of Computer Science 4673, Springer-Verlag, pp. 253-260
2Hamid Sarve, Joakim Lindblad and Carina B. Johansson (2008). Registration of 2D Histological Images of Bone Implants with 3D SRμCT Volumes. In Proceedings of the 4th International Symposium on Visual Computing (ISVC), Las Vegas, USA, Lecture Notes of Computer Science 5358, Springer-Verlag, pp. 1071-1080
3Joakim Lindblad, Nataša Sladoje, Vladimir Curic, Hamid Sarve, Carina B. Johansson and Gunilla Borgefors (2009). Improved quantification of bone remodelling by utilizing fuzzy based segmentation. In Proceedings of the 16th Scandinavian Conference on Image Analysis (SCIA), Oslo, Norway, Lecture Notes of Computer Science 5575, Springer-Verlag, pp. 750-759
4Hamid Sarve, Joakim Lindblad and Carina B. Johansson (2009). Quantification of Bone Remodeling in SRμCT Images of Implants. In Proceedings of the 16th Scandinavian Conference on Image Analysis (SCIA), Oslo, Norway, Lecture Notes of Computer Science 5575, Springer-Verlag, pp. 770-779
5Hamid Sarve, Joakim Lindblad, Gunilla Borgefors and Carina B. Johansson (2010). Methods for Visualization of Bone Tissue in the Proximity of Implants. In Proceedings of the International Conference on Computer Vision and Graphics (ICCVG), Warsaw, Poland,Lecture Notes of Computer Science 6375, Springer-Verlag, pp. 243-250
6Hamid Sarve, Joakim Lindblad, Gunilla Borgefors and Carina B. Johansson (2011). Extracting 3D Information on Bone Remodeling in the Proximity of Titanium Implants in SRμCT Image Volumes. Journal of Computer Methods and Programs in Biomedicine, 102:25-34.
7Hamid Sarve, Bertil Friberg, Gunilla Borgefors, Carina B. Johansson (2011). Introducing a novel analysis technique for osseointegrated dental implants retrieved 29 years post surgery. To appear in Clinical Implant Dentistry and Related Research.
8Hamid Sarve, Amin Allalou and Carina B. Johansson (2011). Cuanto: A Tool for Quantification of Bone Tissue in the Proximity of Implants. Swedish Symposium on Image Analysis 2011, Linköping, Sweden, 4 p.
Place of Publication:Uppsala
Publisher:Centrum för bildanalys, Sveriges lantbruksuniversitet
ISBN for printed version:978-91-576-7605-4
ISSN:1652-6880
Language:English
Publication Type:Doctoral thesis
Full Text Status:Public
Subjects:(A) Swedish standard research categories 2011 > 1 Natural sciences > 102 Computer and Information Science > 10201 Computer Science
(A) Swedish standard research categories 2011 > 1 Natural sciences > 102 Computer and Information Science > Computer Vision and Robotics (Autonomous Systems)
(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 202 Electrical Engineering, Electronic Engineering, Information Engineering > Signal Processing
(A) Swedish standard research categories 2011 > 2 Engineering and Technology > 206 Medical Engineering > Medical Image Processing
Agrovoc terms:image analysis, imagery, digital image processing, implantation
Keywords:image analysis, osseointegration, visualization, SRμCT, bone-implant integration, image registration
URN:NBN:urn:nbn:se:slu:epsilon-m-1
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-m-1
ID Code:8292
Department:(S) > Centre for Image Analysis
External funders:Knowledge Foundation and Swedish Agency for Innovation Systems
Deposited By:INVALID USER
Deposited On:25 Aug 2011 07:39
Metadata Last Modified:02 Dec 2014 10:47

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