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Image analysis of Bone Tissue Remodelling Around Biomaterials
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
2007 (English)In: Medicinteknikdagarna 2007, 2007Conference paper, Published paper (Other (popular science, discussion, etc.))
Abstract [en]

There is a need to develop faster and more reliable histomorphometrical methods for evaluating the implant integration in bone tissue when working on 2D-cut and ground sections. There is a need for reliable 3D methods in order to provide a better insight in bone modelling and remodelling around implants. We foresee that extracting information obtained with different techniques will help us to gain more in our understanding of integration of biomaterials.

We present an automatic method for performing quantitative measurements of implant integration on the histological images. Quantifications involved bone to implant contact as well as bone area inside the threads of the implant. The segmentation was based on discriminant analysis and involved a supervised training where the bone, implant and soft tissue regions has been marked manually. The method is compared to the time consuming and subjective manual measuring of the same features performed in the light-microscope. The area measurements of the automatic method correspond well with the manual method. However, significant difference in the length values of the estimation of the bone to implant contact were observed, revealing greater numbers for the automatic method compared to the manual. These differences are most likely due to staining artifacts.

We also present SR┬ÁCT 3D imaging of samples and observations made so far. The volumes have been segmented using thresholding. The current work involves an improvement of the segmentation in order to obtain correct analysis. Furthermore, manual annotation is very time consuming and difficult for the volumes. In order to work around this deficiency, the 3D samples have been sliced and histologically imaged. These images are easier to annotate and can therefore provide a ground truth. Methods for registration, i.e. finding 2D slice in the 3D volume are being investigated.

Place, publisher, year, edition, pages
2007.
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Analysis
Identifiers
URN: urn:nbn:se:uu:diva-12705OAI: oai:DiVA.org:uu-12705DiVA: diva2:40474
Available from: 2008-01-11 Created: 2008-01-11 Last updated: 2010-01-22Bibliographically approved

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Sarve, Hamid

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