Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
870814 | IRBM | 2014 | 7 Pages |
Abstract
We describe a semi-supervised organ segmentation method for Computed Tomography images. In a first step, a dense oversegmentation of the image is created with an Eikonal-based algorithm. The proposed superpixel algorithm ourperforms state-of-the-art algorithms on classical metrics. In a second step, the semi-supervised segmentation is performed on the underlying Region Adjacency Graph created from the oversegmentation. As the complexity is greatly reduced, the organ segmentation can be performed in real-time.
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Biomedical Engineering
Authors
P. Buyssens, I. Gardin, S. Ruan,