In this paper, we develop a system to classify the outputs of image segmentation algorithms as perceptually relevant or perceptually irrelevant with respect to human perception. T...
In this paper, we introduce a semi-automated segmentation method based on minimizing the Geodesic Active Contour energy incorporating a shape prior. We increase the robustness of t...
Manuel Werlberger, Thomas Pock, Markus Unger, Hors...
The class of geometric deformable models, also known as level sets, has brought tremendous impact to medical imagery due to its capability of topology preservation and fast shape r...
Jasjit S. Suri, Kecheng Liu, Sameer Singh, Swamy L...
Medical volume images contain ambiguous and low-contrast boundaries around which existing fully- or semiautomatic segmentation algorithms often cause errors. In this paper, we pro...
Abstract. In this paper we introduce the concept of statistical deformation models (SDM) which allow the construction of average models of the anatomy and their variability. SDMs a...
Daniel Rueckert, Alejandro F. Frangi, Julia A. Sch...