SIGGRAPH '93 Proceedings of the 20th annual conference on Computer graphics and interactive techniques
Generalized gradient vector flow external forces for active contours
Signal Processing - Special issue on deformable models and techniques for image and signal processing
Extracting Curve Skeletons from Gray Value Images for Virtual Endoscopy
MIAR '08 Proceedings of the 4th international workshop on Medical Imaging and Augmented Reality
3D object segmentation using B-Surface
Image and Vision Computing
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This paper develops a 3D automated approach for airway wall segmentation and quantification inMSCT based on a patient-specific deformable model. The model is explicitly defined as a triangular surface mesh at the level of the airway lumen segmented from the MSCT data. The model evolves according to simplified Lagrangian dynamics, where the deformation force field is defined by a case-specific generalized gradient vector flow. Such force formulation allows locally adaptive time step integration and prevents model self-intersections. The evaluations performed on simulated and clinical MSCT data have shown a good agreement with the radiologist expertise and underlined a higher potential of the proposed 3D approach for the study of airway remodeling versus 2D cross-section techniques.