International Journal of Computer Vision
Global Minimum for Active Contour Models: A Minimal Path Approach
International Journal of Computer Vision
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pattern Recognition Letters
Contour and Texture Analysis for Image Segmentation
International Journal of Computer Vision
JPEG 2000: Image Compression Fundamentals, Standards and Practice
JPEG 2000: Image Compression Fundamentals, Standards and Practice
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Digital Coding of Waveforms: Principles and Applications to Speech and Video
Geometric Level Set Methods in Imaging,Vision,and Graphics
Geometric Level Set Methods in Imaging,Vision,and Graphics
Graph Cuts and Efficient N-D Image Segmentation
International Journal of Computer Vision
The Journal of Machine Learning Research
Level Set Based Surface Capturing in 3D Medical Images
MICCAI '08 Proceedings of the 11th international conference on Medical Image Computing and Computer-Assisted Intervention - Part I
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mumford-Shah regularizer with contextual feedback
Journal of Mathematical Imaging and Vision
Prior knowledge driven multiscale segmentation of brain MRI
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
Is a single energy functional sufficient? adaptive energy functionals and automatic initialization
MICCAI'07 Proceedings of the 10th international conference on Medical image computing and computer-assisted intervention
IEEE Transactions on Image Processing
Reliability-driven, spatially-adaptive regularization for deformable registration
WBIR'10 Proceedings of the 4th international conference on Biomedical image registration
Adaptive regularization for image segmentation using local image curvature cues
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part IV
Statistical significance based graph cut segmentation for shrinking bias
ICIAR'11 Proceedings of the 8th international conference on Image analysis and recognition - Volume Part I
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Image segmentation techniques are predominately based on parameter-laden optimization processes. The segmentation objective function traditionally involves parameters (i.e. weights) that need to be tuned in order to balance the underlying competing cost terms of image data fidelity and contour regularization. In this paper, we propose a novel approach for automatic adaptive energy parameterization. In particular, our contributions are three-fold; 1) We spatially adapt fidelity and regularization weights to local image content in an autonomous manner. 2) We modulate the weight using a novel contextual measure of image quality based on the concept of spectral flatness. 3) We incorporate our proposed parameterization into a general segmentation framework and demonstrate its superiority to two alternative approaches: the best possible spatially-fixed parameterization and the globally optimal spatially-varying, but non- contextual, parameters. Our segmentation results are evaluated on real and synthetic data and produce a reduction in mean segmentation error when compared to alternative approaches.