Author:

Keywords:

Science & Technology, Technology, Computer Science, Artificial Intelligence, Engineering, Electrical & Electronic, Computer Science, Engineering, Active contours, B-splines, image segmentation, real-time image processing, variational method, IMAGE SEGMENTATION, ULTRASOUND IMAGES, LEVEL-SET, CONTOURS, REGISTRATION, EVOLUTION, DRIVEN, Algorithms, Diagnostic Imaging, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Numerical Analysis, Computer-Assisted, Pattern Recognition, Automated, Reproducibility of Results, Sensitivity and Specificity, 0801 Artificial Intelligence and Image Processing, 0906 Electrical and Electronic Engineering, 1702 Cognitive Sciences, Artificial Intelligence & Image Processing, 4603 Computer vision and multimedia computation, 4607 Graphics, augmented reality and games

Abstract:

A new formulation of active contours based on explicit functions has been recently suggested. This novel framework allows real-time 3-D segmentation since it reduces the dimensionality of the segmentation problem. In this paper, we propose a B-spline formulation of this approach, which further improves the computational efficiency of the algorithm. We also show that this framework allows evolving the active contour using local region-based terms, thereby overcoming the limitations of the original method while preserving computational speed. The feasibility of real-time 3-D segmentation is demonstrated using simulated and medical data such as liver computer tomography and cardiac ultrasound images.