Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
A fast level set method for propagating interfaces
Journal of Computational Physics
A variational level set approach to multiphase motion
Journal of Computational Physics
International Journal of Computer Vision
A Level Set Model for Image Classification
International Journal of Computer Vision
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
International Journal of Computer Vision
Using Prior Shapes in Geometric Active Contours in a Variational Framework
International Journal of Computer Vision
International Journal of Computer Vision
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
A Statistical Approach to Snakes for Bimodal and Trimodal Imagery
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
A Geometric Approach to Segmentation and Analysis of 3D Medical Images
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Statistical models in medical image analysis
Statistical models in medical image analysis
Non-rigid registration using distance functions
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Towards recognition-based variational segmentation using shape priors and dynamic labeling
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
IEEE Transactions on Image Processing
International Journal of Computer Vision
Joint Parametric and Non-parametric Curve Evolution for Medical Image Segmentation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Multi-Reference Shape Priors for Active Contours
International Journal of Computer Vision
Cooperative Object Segmentation and Behavior Inference in Image Sequences
International Journal of Computer Vision
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Region based image segmentation using a modified Mumford-Shah algorithm
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
The multiplicative path toward prior-shape guided active contour for object detection
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Study and application of medical image visualization technology
ICDHM'07 Proceedings of the 1st international conference on Digital human modeling
Segmentation using the edge strength function as a shape prior within a local deformation model
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Review article: Edge and line oriented contour detection: State of the art
Image and Vision Computing
Segmentation for hyperspectral images with priors
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part II
Tracking objects using shape context matching
Neurocomputing
Real-Time 3d image segmentation by user-constrained template deformation
MICCAI'12 Proceedings of the 15th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Extraction of left ventricle borders with local and global priors from echocardiograms
Machine Vision and Applications
Machine Vision and Applications
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In this paper, we propose a new variational model to segment an object belonging to a given shape space using the active contour method, a geometric shape prior and the Mumford-Shah functional. The core of our model is an energy functional composed by three complementary terms. The first one is based on a shape model which constrains the active contour to get a shape of interest. The second term detects object boundaries from image gradients. And the third term drives globally the shape prior and the active contour towards a homogeneous intensity region. The segmentation of the object of interest is given by the minimum of our energy functional. This minimum is computed with the calculus of variations and the gradient descent method that provide a system of evolution equations solved with the well-known level set method. We also prove the existence of this minimum in the space of functions with bounded variation. Applications of the proposed model are presented on synthetic and medical images.