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“School of Cognitive Sciences”

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Paper   IPM / Cognitive Sciences / 8482
School of Cognitive Sciences
  Title:   Interactive Coupled Object Segmentation Using Symmetry and Distance Constraints
1.  P. Bahman Bijari
2.  A. Akhundi Asl
3.  H. Soltanian-Zadeh
  Status:   In Proceedings
  Proceeding: Cairo international Biomedical Engineering Conference
  Year:  2006
  Supported by:  IPM
In this paper, we introduce a novel interactive method based on symmetry and distance constraints for the segmentation of medical images. Our new symmetry interaction and distance constraint are integrated with the Herbulot�s entropy minimization and Chen�s shape-prior segmentation methods. This incorporates knowledge-based constraints that increase the accuracy and reduce the initialization dependency. We applied our algorithm to segment ventricle and caudate in magnetic resonance images (MRI) of the brain. Comparative results show the effects of the proposed constraints. More accurate results and less dependency to initialization are obtained when using the proposed method.

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