Last update : March 3, 2000

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Publications by Antonio M. López Peña (Computer Vision Center, Universitat Autònoma de Barcelona (UAB)) et al. on ridges and related topics :

• Evaluation of Methods for Ridge and Valley Detection, A. M. López et al., PAMI 1999.
• Creaseness-based CT and MR registration: Comparison with the mutual information method, D. Lloret, A. M. López, J. Serrat, Journal of Electronic Imaging, 1999
• Creaseness from Level Set Extrinsic Curvature, A. M. López et al., 1998.
• Creaseness for CT and MR Image Registration, A. M. López et al., 1998.

On-line notes:

• CVonline: Ridge/Valley-like structures: Creases, separatrices and drainage patterns. A. M. López, 1997.

BibTeX references.

Ridges and valleys are useful geometric features for image analysis. Different characterizations have been proposed to formalize the intuitive notion of ridge/valley. In this paper, we review their principal characterizations and propose a new one. Subsequently, we evaluate these characterizations with respect to a list of desirable properties and their purpose in the context of representative image analysis tasks.

Index Terms: Creases, separatrices, drainage patterns, comparative analysis.

This paper describes a method which uses the skull as a landmark for automatic registration of CT to MR images. First, the skull is extracted from both images using a new creaseness operator. Then, the resulting creaseness images are used to build a hierarchic structure which permits a robust and fast search. We have justified experimentally the performance of several choices of our algorithm, and we have thoroughly tested its accuracy and roughness against the well-known mutual information method for 5 different pairs of images. We have found both comparable, and for certain MR images the proposed method achieves better performance.

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