Coupled Parametric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
An active contour model for image segmentation based on elastic interaction
Journal of Computational Physics
Journal of Mathematical Imaging and Vision
Locally regularized smoothing B-snake
EURASIP Journal on Applied Signal Processing
Joint co-clustering: Co-clustering of genomic and clinical bioimaging data
Computers & Mathematics with Applications
Anisotropic virtual electric field for active contours
Pattern Recognition Letters
Contour Extraction Algorithm Using a Robust Neural Network
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part IV: ICCS 2007
Nonparametric Level-Set Segmentation Based on the Minimization of the Stochastic Complexity
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Effect of Number of Coupled Structures on the Segmentation of Brain Structures
Journal of Signal Processing Systems
Robust B-spline Snakes For Ultrasound Image Segmentation
Journal of Signal Processing Systems
Narrow band region-based active contours and surfaces for 2D and 3D segmentation
Computer Vision and Image Understanding
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
Stabilization of parametric active contours using a tangential redistribution term
IEEE Transactions on Image Processing
OLYBIA: ontology-based automatic image annotation system using semantic inference rules
DASFAA'07 Proceedings of the 12th international conference on Database systems for advanced applications
Automated segmentation of tissue images for computerized IHC analysis
Computer Methods and Programs in Biomedicine
A novel material decomposition algorithm for multienergy x-ray radiography systems
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Expert Systems with Applications: An International Journal
Computer-aided techniques for chromogenic immunohistochemistry: Status and directions
Computers in Biology and Medicine
Computer Graphics in China: Convergence analysis for B-spline geometric interpolation
Computers and Graphics
Effective elliptic fitting for iris normalization
Computer Vision and Image Understanding
Reconstruction from non-uniform samples: A direct, variational approach in shift-invariant spaces
Digital Signal Processing
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Parametric active contour models are one of the preferred approaches for image segmentation because of their computational efficiency and simplicity. However, they have a few drawbacks which limit their performance. In this paper, we identify some of these problems and propose efficient solutions to get around them. The widely-used gradient magnitude-based energy is parameter dependent; its use will negatively affect the parametrization of the curve and, consequently, its stiffness. Hence, we introduce a new edge-based energy that is independent of the parameterization. It is also more robust since it takes into account the gradient direction as well. We express this energy term as a surface integral, thus unifying it naturally with the region-based schemes. The unified framework enables the user to tune the image energy to the application at hand. We show that parametric snakes can guarantee low curvature curves, but only if they are described in the curvilinear abscissa. Since normal curve evolution do not ensure constant arc-length, we propose a new internal energy term that will force this configuration. The curve evolution can sometimes give rise to closed loops in the contour, which will adversely interfere with the optimization algorithm. We propose a curve evolution scheme that prevents this condition.