Stochastic simulation
Cooling schedules for optimal annealing
Mathematics of Operations Research
Using Dynamic Programming for Solving Variational Problems in Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
Dynamic segmentation: finding the edge with snake splines
Curves and surfaces
A Cost Minimization Approach to Edge Detection Using Simulated Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast algorithm for active contours and curvature estimation
CVGIP: Image Understanding
Extraction of Straight Lines in Aerial Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Using deformable surfaces to segment 3-D images and infer differential structures
CVGIP: Image Understanding
Object Matching Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vehicle Segmentation and Classification Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
"Brownian Strings": Segmenting Images with Stochastically Deformable Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Discrete-time CNN for image segmentation by active contours
Pattern Recognition Letters
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
Global and Local Active Contours for Head Boundary Extraction
International Journal of Computer Vision
Statistical Region Snake-Based Segmentation Adapted to Different Physical Noise Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable Shape Detection and Description via Model-Based Region Grouping
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bayesian Object Localisation in Images
International Journal of Computer Vision
Semi-Automated Extraction of Rivers from Digital Imagery
Geoinformatica
Probabilistic Tracking with Exemplars in a Metric Space
International Journal of Computer Vision - Marr Prize Special Issue
On shape detection in noisy images with particular reference to ultrasonography
Statistics and Computing
A Robust Snake Implementation; A Dual Active Contour
IEEE Transactions on Pattern Analysis and Machine Intelligence
Graphical Gaussian Shape Models and Their Application to Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape-Guided Split and Merge of Image Regions
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Shape Tracking Using Centroid-Based Methods
EMMCVPR '01 Proceedings of the Third International Workshop on Energy Minimization Methods in Computer Vision and Pattern Recognition
A Bayesian Approach to in vivo Kidney Ultrasound Contour Detection Using Markov Random Fields
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Automatic Deformable Shape Segmentation for Image Database Search Applications
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
Deformable Contour Method: A Constrained Optimization Approach
International Journal of Computer Vision
International Journal of Computer Vision
Integrating prior shape models into level-set approaches
Pattern Recognition Letters
Influence of the Noise Model on Level Set Active Contour Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
CPM: A Deformable Model for Shape Recovery and Segmentation Based on Charged Particles
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stochastic Motion and the Level Set Method in Computer Vision: Stochastic Active Contours
International Journal of Computer Vision
Review: A comparative study of deformable contour methods on medical image segmentation
Image and Vision Computing
Boundary Detection in Echocardiographic Images Using Markovian Level Set Method
IEICE - Transactions on Information and Systems
Multiple genetic snakes for people segmentation in video sequences
SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis
Multiple genetic snakes for bone segmentation
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
Applied Stochastic Models in Business and Industry
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In many applications of image analysis, simply connected objects are to be located in noisy images. During the last 5-6 years active contour models have become popular for finding the contours of such objects. Connected to these models are iterative algorithms for finding the minimizing energy curves making the curves behave dynamically through the iterations. These approaches do however have several disadvantages. The numerical algorithms that are in use constrain the models that can be used. Furthermore, in many cases only local minima can be achieved. In this paper, the author discusses a method for curve detection based on a fully Bayesian approach. A model for image contours which allows the number of nodes on the contours to vary is introduced. Iterative algorithms based on stochastic sampling is constructed, which make it possible to simulate samples from the posterior distribution, making estimates and uncertainty measures of specific quantities available. Further, simulated annealing schemes making the curve move dynamically towards the global minimum energy configuration are presented. In theory, no restrictions on the models are made. In practice, however, computational aspects must be taken into consideration when choosing the models. Much more general models than the one used for active contours may however be applied. The approach is applied to ultrasound images of the left ventricle and to magnetic resonance images of the human brain, and show promising results.