Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
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
Geodesic Active Contours and Level Sets for the Detection and Tracking of Moving Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Level Set Evolution without Re-Initialization: A New Variational Formulation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Multiscale Joint Segmentation and Registration of Image Morphology
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Statistical Active Contour Model for Noisy Image Segmentation
CISP '08 Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 3 - Volume 03
Efficient and reliable schemes for nonlinear diffusion filtering
IEEE Transactions on Image Processing
Fourth-order partial differential equations for noise removal
IEEE Transactions on Image Processing
The digital TV filter and nonlinear denoising
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Image segmentation and selective smoothing by using Mumford-Shah model
IEEE Transactions on Image Processing
PDE-based image restoration: a hybrid model and color image denoising
IEEE Transactions on Image Processing
Active Contour External Force Using Vector Field Convolution for Image Segmentation
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Edge Grouping Combining Boundary and Region Information
IEEE Transactions on Image Processing
Image Segmentation Using Active Contours Driven by the Bhattacharyya Gradient Flow
IEEE Transactions on Image Processing
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This paper addresses the segmentation and smoothing problems in biomedical imaging under variational framework. In order to get better results, this paper proposes a new segmentation and selective smoothing algorithm. This paper has the following three contributions. First, a new statistical active contour model (SACM) is introduced for noisy image segmentation. SACM is proposed to solve the problem in fast edge integration (FEI) method, which takes advantages of both edge-based and region-based active contour model but only considers the mean information inside and outside of the evolution curve. In SACM, a new statistical term for considering the probability distribution density of regions and a unified variational framework are proposed for construction of different segmentation models with different probability density functions. Moreover, a penalized term is also introduced in the proposed model as internal energy in order to avoid the time consuming re-initialization process. Second, a new symmetric fourth-order PDE denoising algorithm is developed to avoid the blocky effects in second-order PDE model, while preserving edges. Third, in each stage of segmentation process, different denoising algorithms (or different parameters in the same denoising model) can be employed for different sub-regions independently, so that better segmentation and smoothing results can be obtained. Compared with existing methods, our method is more flexible, robust to noise, computationally efficient and produces better results.