Interactive Image Segmentation Using Elastic Interpolation

Abstract

Elastic body splines (EBS) belong to a family of splines introduced for biomedical image registration. EBS models the elastic deformation of a homogeneous isotropic elastic body subjected to external forces. The task of interactive image segmentation is framed as a semi-supervised interpolation where the basis functions are learned using the user provided seed points to model and predict the labels for the unlabeled pixels. Seed points are sparse compared to other methods that may require scribbles and regions. The spline for interpolating labels is the EBS which we compare to our previous work using Gaussian Elastic Body splines (GEBS) [1] for the task of interactive image segmentation. Experimental results show that the EBS is about 14 percent better, in terms of accuracy, than GEBS and significantly better than random walk and graph cut based segmentation. EBS is also 2.5 times faster than GEBS.