Recovery of Parametric Models from Range Images: The Case for Superquadrics with Global Deformations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution stochastic hybrid shape models with fractal priors
ACM Transactions on Graphics (TOG) - Special issue on interactive sculpting
A level set approach for computing solutions to incompressible two-phase flow
Journal of Computational Physics
Active shape models—their training and application
Computer Vision and Image Understanding
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
A survey of free-form object representation and recognition techniques
Computer Vision and Image Understanding
Using Prior Shapes in Geometric Active Contours in a Variational Framework
International Journal of Computer Vision
Shape Priors for Level Set Representations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Level Set Based Segmentation with Intensity and Curvature Priors
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
On the Incorporation of shape priors into geometric active contours
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Approximations of Shape Metrics and Application to Shape Warping and Empirical Shape Statistics
Foundations of Computational Mathematics
Fast Global Minimization of the Active Contour/Snake Model
Journal of Mathematical Imaging and Vision
The Split Bregman Method for L1-Regularized Problems
SIAM Journal on Imaging Sciences
Geometric Applications of the Split Bregman Method: Segmentation and Surface Reconstruction
Journal of Scientific Computing
Robust bilayer video segmentation by adaptive propagation of global shape and local appearance
Journal of Visual Communication and Image Representation
Efficient kernel density estimation of shape and intensity priors for level set segmentation
MICCAI'05 Proceedings of the 8th international conference on Medical image computing and computer-assisted intervention - Volume Part II
Evaluation of segmentation techniques using region area and boundary matching information
Journal of Visual Communication and Image Representation
Segmentation of images with separating layers by fuzzy c-means and convex optimization
Journal of Visual Communication and Image Representation
Total variation blind deconvolution
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Reduced set density estimator for object segmentation based on shape probabilistic representation
Journal of Visual Communication and Image Representation
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In this paper, we focus on segmentation of ultrasound kidney images. Unlike previous work by using trained prior shapes, we employ a parametric super-ellipse as a global prior shape for a human kidney. The Fisher-Tippett distribution is employed to describe the grey level statistics. Combining the grey level statistics with a global character of a kidney shape, we propose a new active contour model to segment ultrasound kidney images. The proposed model involves two subproblems. One subproblem is to optimize the parameters of a super-ellipse. Another subproblem is to segment an ultrasound kidney image. An alternating minimization scheme is used to optimize the parameters of a super-ellipse and segment an image simultaneously. To segment an image fast, a convex relaxation method is introduced and the split Bregman method is incorporated to propose a fast segmentation algorithm. The efficiency of the proposed method is illustrated by numerical experiments on both simulated images and real ultrasound kidney images.