Region Competition via Local Watershed Operators
- 27 July 2005
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
In this paper, we propose a segmentation algorithm which combines the ideas from local watershed transforms and the region based deformable models. Traditionally, watersheds are computed in the whole image and then some region merging techniques are applied on them to reach the segmentation of structures. We propose that watershed regions can be used as operators in region-based deformable models. These regions are computed only when the deformable models reach them. Then, they are added to (or subtracted from) the deformable models via a measure computed from two terms: (i) statistical fit of regions to the models, region competition; (ii) smoothness of such fits, smoothness constraint. The proposed algorithm is computationally efficient because it operates on regions instead of pixels. In addition, this algorithm allows better boundary localization due to the edge information brought by watersheds. Moreover, the proposed algorithm can handle topological changes, e.g., split or merge, during the evolutions without an additional embedded surface as in the case of level set formulation. Furthermore, structure-based smoothness of segmented objects is obtained by using the smoothness term computed from the alignment of regions. We illustrate the efficiency and accuracy of the proposed technique on several medical data such as MRA and CTA data.Keywords
This publication has 17 references indexed in Scilit:
- A vertex-based representation of objects in an imagePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Segmentation of carpal bones from CT images using skeletally coupled deformable modelsMedical Image Analysis, 2002
- Image segmentation by reaction-diffusion bubblesPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Algorithms for implicit deformable modelsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- A statistical approach to snakes for bimodal and trimodal imageryPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1999
- An Active Contour Model without EdgesLecture Notes in Computer Science, 1999
- Area and length minimizing flows for shape segmentationIEEE Transactions on Image Processing, 1998
- Region competition: unifying snakes, region growing, and Bayes/MDL for multiband image segmentationIeee Transactions On Pattern Analysis and Machine Intelligence, 1996
- Watersheds in digital spaces: an efficient algorithm based on immersion simulationsIeee Transactions On Pattern Analysis and Machine Intelligence, 1991
- Snakes: Active contour modelsInternational Journal of Computer Vision, 1988