Motion Segmentation and Tracking Using Normalized Cuts
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Multilevel Banded Graph Cuts Method for Fast Image Segmentation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Graph Cuts and Efficient N-D Image Segmentation
International Journal of Computer Vision
The Visual Computer: International Journal of Computer Graphics
Video SnapCut: robust video object cutout using localized classifiers
ACM SIGGRAPH 2009 papers
Near real-time motion segmentation using graph cuts
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
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With the increasing availability of 4D cardiac imaging technologies, the need for efficient spatio-temporal segmentation algorithms for the heart is growing. We propose a new method for heart segmentation in 4D data sets. We efficiently use the established graph cut method for the segmentation of the heart by simultaneously exploiting motion and region cues. We construct a 4D graph designed to find a moving object with a uniform intensity from a static background. This method has useful applications ranging from qualitative tasks such as direct visualization of the heart by removing its surrounding structures, to quantitative tasks such as measurements and analysis of the total heart volume. The method has been tested on cardiac MRI sequences with successful results.