Adapting Active Shape Models for 3D Segmentation of Tubular Structures in Medical Images

Active Shape Models (ASM) have proven to be an effective approach for image segmentation. In some applications, however, the linear model of gray level appearance around a contour that is used in ASM is not sufficient for accurate boundary localization. Furthermore, the statistical shape model may be too restricted if the training set is limited. This paper describes modifications to both the shape and the appearance model of the original ASM formulation. Shape model flexibility is increased, for tubular objects, by modeling the axis deformation independent of the cross-sectional deformation, and by adding supplementary cylindrical deformation modes. Furthermore, a novel appearance modeling scheme that effectively deals with a highly varying background is developed. In contrast with the conventional ASM approach, the new appearance model is trained on both boundary and non-boundary points, and the probability that a given point belongs to the boundary is estimated non-parametrically. T...

• Type: Conference
• Year: 2003
• Where: IPMI
• Authors: Marleen de Bruijne, Bram van Ginneken, Max A. Viergever, Wiro J. Niessen
• Keywords: IPMI 2003, Medical Imaging, Shape Model Extensions, Shape Model Flexibility, Statistical Shape Model