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Optimal RANSAC - Towards a Repeatable Algorithm for Finding the Optimal Set
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
2013 (English)In: Journal of WSCG, ISSN 1213-6972, E-ISSN 1213-6964, Vol. 21, no 1, 21-30 p.Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2013. Vol. 21, no 1, 21-30 p.
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Computerized Image Processing
Identifiers
URN: urn:nbn:se:uu:diva-200593OAI: oai:DiVA.org:uu-200593DiVA: diva2:624363
Conference
International Conferences in Central Europe on Computer Graphics, Visualization and Computer Vision
Available from: 2013-05-31 Created: 2013-05-31 Last updated: 2017-12-06Bibliographically approved
In thesis
1. Interactive 3D Image Analysis for Cranio-Maxillofacial Surgery Planning and Orthopedic Applications
Open this publication in new window or tab >>Interactive 3D Image Analysis for Cranio-Maxillofacial Surgery Planning and Orthopedic Applications
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Modern medical imaging devices are able to generate highly detailed three-dimensional (3D) images of the skeleton. Computerized image processing and analysis methods, combined with real-time volume visualization techniques, can greatly facilitate the interpretation of such images and are increasingly used in surgical planning to aid reconstruction of the skeleton after trauma or disease. Two key challenges are to accurately separate (segment) bone structures or cavities of interest from the rest of the image and to interact with the 3D data in an efficient way. This thesis presents efficient and precise interactive methods for segmenting, visualizing, and analysing 3D computed tomography (CT) images of the skeleton. The methods are validated on real CT datasets and are primarily intended to support planning and evaluation of cranio-maxillofacial (CMF) and orthopedic surgery.

Two interactive methods for segmenting the orbit (eye-socket) are introduced. The first method implements a deformable model that is guided and fitted to the orbit via haptic 3D interaction, whereas the second method implements a user-steered volumetric brush that uses distance and gradient information to find exact object boundaries.

The thesis also presents a semi-automatic method for measuring 3D angulation changes in wrist fractures. The fractured bone is extracted with interactive mesh segmentation, and the angulation is determined with a technique based on surface registration and RANSAC.

Lastly, the thesis presents an interactive and intuitive tool for segmenting individual bones and bone fragments. This type of segmentation is essential for virtual surgery planning, but takes several hours to perform with conventional manual methods. The presented tool combines GPU-accelerated random walks segmentation with direct volume rendering and interactive 3D texture painting to enable quick marking and separation of bone structures. It enables the user to produce an accurate segmentation within a few minutes, thereby removing a major bottleneck in the planning procedure.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2016. 58 p.
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1411
Keyword
medical image analysis, interactive segmentation, volume rendering, computed tomography
National Category
Computer Science Medical Image Processing
Research subject
Computerized Image Processing
Identifiers
urn:nbn:se:uu:diva-301180 (URN)978-91-554-9668-5 (ISBN)
External cooperation:
Public defence
2016-09-30, ITC 2446, Lägerhyddsvägen 2, Uppsala, 10:15 (English)
Opponent
Supervisors
Available from: 2016-09-09 Created: 2016-08-19 Last updated: 2016-09-13

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Hast, AndersNysjö, Johan

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