4D deformable models with temporal constraints: application to 4D cardiac image segmentation

Space and Time Shape Constrained

The aim of this work is to automatically extract quantitative parameters from time sequences of 3D images (4D images) suited to heart pathology diagnosis. In this paper, we propose a framework for the reconstruction of the left ventricle motion from 4D images based on 4D deformable surface models. These 4D models are represented as a time sequence of 3D meshes whose deformation are correlated d...

Space and Time Shape Constrained Deformable Surfaces for 4D Medical Image Segmentation

The heart motion study is vital for the understanding and the early diagnosis of cardiac pathologies that remain the primary cause of death in western countries to date. Heart motion analysis require the extraction of quantitative parameters from time sequences of 3D images (4D images) such as volume, sep-tum wall thickness, ejection fraction and motion amplitude. In this paper, we propose a fr...

4D Endocardial Segmentation Using Spatio-temporal Appearance Models and Level Sets

In this paper a framework for the segmentation of cardiac MR image sequences using spatio-temporal appearance models is presented. The method splits the 4D space into 2 separate subspaces, one for changes in appearance and one subspace for changes in motion. Using the 4D appearance models in combination with a level set framework combines the robustness of model based segmentation with the flex...

Spatial and temporal shape constrained deformable surfaces for 3D and 4D medical image segmentation

Real-time segmentation by Active Geometric Functions

Recent advances in 4D imaging and real-time imaging provide image data with clinically important cardiac dynamic information at high spatial or temporal resolution. However, the enormous amount of information contained in these data has also raised a challenge for traditional image analysis algorithms in terms of efficiency. In this paper, a novel deformable model framework, Active Geometric Fu...