Song, Y, Brodlie, KW and Bulpitt, AJ (2008) Efficient semi-automatic segmentation for creating patient specific models for virtual environments. In: 2nd MICCAI Workshop on Computer Vision for Intravascular and Intracardiac Imaging. 2nd MICCAI Workshop on Computer Vision for Intravascular and Intracardiac Imaging, 30th September 2008, Kimmel Center, New York University NYC, USA. , pp. 22-34.
Abstract
There is an increasing demand for the development of virtual environments for training in vascular interventional radiological procedures. This requires fast and precise segmentation of varied abdominal structures from a wide range of image modalities. This paper presents an efficient semi-automatic segmentation system which combines image processing techniques and mathematical morphology operations to obtain an initial segmentation close to the target structure shape. This initial segmentation is then embedded into a level set function to obtain a refined segmentation result. Minimal intervention is required in comparison to other level set based approaches. The approach also dramatically decreases processing time and reduces the risks of leaking at weak boundaries, without compromising the accuracy of the segmentation.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) > Artificial Intelligence & Biological Systems (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 11 Mar 2014 13:13 |
Last Modified: | 15 Sep 2014 01:49 |
Published Version: | http://vpa.sabanciuniv.edu.tr/sites/cvii2008/CVII2... |
Status: | Published |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:78000 |