Narrow band region-based active contours and surfaces for 2D and 3D segmentation
Computer Vision and Image Understanding
A Local Normal-Based Region Term for Active Contours
EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Organ Segmentation with Level Sets Using Local Shape and Appearance Priors
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Active contour model driven by local histogram fitting energy
Pattern Recognition Letters
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Recently, new segmentation models based on local information have emerged. They combine local statistics of the regions along the contour (inside and outside) to drive the segmentation procedure. Since they are based on local decisions, these models are more robust to local variations of the regions of interest (contrast, noise, blur, ...). They nonetheless also introduce some new difficulties which are inherent to the fact of basing a global property (the segmentation) on pure local decisions. This papers explores some of those difficulties and proposes some possible corrections. Results on both 2D and 3D data are compared to those obtained without these corrections.