International Journal of Computer Vision
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
A new supervised evaluation criterion for region based segmentation methods
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
IEEE Transactions on Image Processing
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There is a great deal of interest in developing automated histological grading of tissue biopsies. Current approaches involve sophisticated algorithms for image segmentation, tissue architecture characterization, global texture feature extraction, and high-dimensional clustering and classification algorithms. Although overall image classification accuracy is measured, there has been very little attention paid to the quantitative assessment of the image segmentation stage (glandular structure characterization stage) to provide feedback to the segmentation process. We describe a robust approach for tissue segmentation combining spatial clustering with multiphase vector level set active contours to extract nuclei, lumen and epithelial cytoplasm. Quantitative segmentation performance compared to manual ground truth is assessed using region-based geometric criteria.