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.