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Topological Active Volume 3D segmentation model optimized with genetic approaches

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Abstract

The Topological Active Volumes is an active model focused on 3D segmentation tasks. It is based on the 2D Topological Active Nets model and provides information about the surfaces and the inside of the detected objects in the scene. This paper proposes new optimization approaches based on Genetic Algorithms that improve the results of the 3D segmentations and overcome some drawbacks of the model related to parameter tuning or noise conditions. The hybridization of the genetic algorithm with a greedy local search allows the treatment of topological changes in the model, with the possibility of an automatic subdivision of the Topological Active Volume. This combination integrates the advantages of the global and local search procedures in the segmentation process.

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Acknowledgments

This paper was funded by the Ministry of Science and Innovation of Spain through project TIN2007-64330 and by the Instituto de Salud Carlos III through the grant contract PI08/90420 using FEDER funds.

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Authors and Affiliations

  1. Department of Computer Science, University of A Coruña, Campus de Elviña s/n, 15071, Coruña, Spain

    Jorge Novo, Noelia Barreira, Manuel González Penedo & José Santos

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  1. Jorge Novo
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  2. Noelia Barreira
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  3. Manuel González Penedo
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  4. José Santos
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Correspondence to Jorge Novo.

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Novo, J., Barreira, N., Penedo, M.G. et al. Topological Active Volume 3D segmentation model optimized with genetic approaches. Nat Comput 11, 161–174 (2012). https://doi.org/10.1007/s11047-011-9275-8

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