Recursive region splitting at hierarchical scope views
Computer Vision, Graphics, and Image Processing
Evaluation and comparison of different segmentation algorithms
Pattern Recognition Letters
Different Learning Strategies in a Case-Based Reasoning System for Image Interpretation
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
CBR-Based Ultra Sonic Image Interpretation
EWCBR '00 Proceedings of the 5th European Workshop on Advances in Case-Based Reasoning
Why Case-Based Reasoning Is Attractive for Image Interpretation
ICCBR '01 Proceedings of the 4th International Conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Realizing Modularized Knowledge Models for Heterogeneous Application Domains
ICDM '08 Proceedings of the 8th industrial conference on Advances in Data Mining: Medical Applications, E-Commerce, Marketing, and Theoretical Aspects
An Analysis of Research Themes in the CBR Conference Literature
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
Case-based reasoning emulation of persons for wheelchair navigation
Artificial Intelligence in Medicine
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Image Segmentation is a crucial step if extracting information from a digital image. It is not easy to set up the segmentation parameter so that it fits best over the entire set of images, which should be segmented. In the paper, we propose a novel architecture for image segmentation method based on CBR, which can adapt to changing image qualities and environmental conditions. We describe the whole architecture, the methods used for the various components of the systems and show how it performs on medical images.