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Fast and robust semi-automatic liver segmentation with haptic interaction
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.
2006 (English)In: Proceedings of Medical Image Computing and Computer-Assisted Intervention, LNCS, ISSN 0302-9743, Vol. 4191, 774-781 p.Article in journal (Refereed) Published
Place, publisher, year, edition, pages
2006. Vol. 4191, 774-781 p.
URN: urn:nbn:se:uu:diva-96641OAI: oai:DiVA.org:uu-96641DiVA: diva2:171282
Available from: 2008-01-18 Created: 2008-01-18 Last updated: 2016-01-08Bibliographically approved
In thesis
1. Visualization and Haptics for Interactive Medical Image Analysis
Open this publication in new window or tab >>Visualization and Haptics for Interactive Medical Image Analysis
2008 (English)Doctoral thesis, comprehensive summary (Other academic)
Alternative title[sv]
Visualisering och Haptik för Interaktiv Medicinsk Bildanalys
Abstract [en]

Modern medical imaging techniques provide an increasing amount of high-dimensional and high-resolution image data that need to be visualized, analyzed, and interpreted for diagnostic and treatment planning purposes. As a consequence, efficient ways of exploring these images are needed. In order to work with specific patient cases, it is necessary to be able to work directly with the medical image volumes and to generate the relevant 3D structures directly as they are needed for visualization and analysis. This requires efficient tools for segmentation, i.e., separation of objects from each other and from the background. Segmentation is hard to automate due to, e.g., high shape variability of organs and limited contrast between tissues. Manual segmentation, on the other hand, is tedious and error-prone. An approach combining the merits from automatic and manual methods is semi-automatic segmentation, where the user interactively provides input to the methods. For complex medical image volumes, the interactive part can be highly 3D oriented and is therefore dependent on the user interface.

This thesis presents methods for interactive segmentation and visualization where true 3D interaction with haptic feedback and stereo graphics is used. Well-known segmentation methods such as fast marching, fuzzy connectedness, live-wire, and deformable models, have been tailored and extended for implementation in a 3D environment where volume visualization and haptics are used to guide the user. The visualization is accelerated with graphics hardware and therefore allows for volume rendering in stereo at interactive rates. The haptic feedback is rendered with constraint-based direct volume haptics in order to convey information about the data that is hard to visualize and thereby facilitate the interaction. The methods have been applied to real medical images, e.g., 3D liver CT data and 4D breast MR data with good results. To provide a tool for future work in this area, a software toolkit containing the implementations of the developed methods has been made publicly available.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2008. 83 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 386
Bildanalys, medical image analysis, haptic rendering, volume visualization, interactive segmentation, Bildanalys
urn:nbn:se:uu:diva-8409 (URN)978-91-554-7067-8 (ISBN)
Public defence
2008-02-08, Häggsalen, Ångströmlaboratoriet, Polacksbacken, Uppsala, 10:15 (English)
Available from: 2008-01-18 Created: 2008-01-18 Last updated: 2010-05-12Bibliographically approved

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