Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Automated 3D Segmentation Using Deformable Models and Fuzzy Affinity
IPMI '97 Proceedings of the 15th International Conference on Information Processing in Medical Imaging
Modelling Elasticity in Solids Using Active Cubes - Application to Simulated Operations
CVRMed '95 Proceedings of the First International Conference on Computer Vision, Virtual Reality and Robotics in Medicine
EURASIP Journal on Applied Signal Processing
Genetic-Greedy Hybrid Approach for Topological Active Nets Optimization
ICANNGA '07 Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part I
Genetic approaches for topological active nets optimization
Pattern Recognition
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
Topological Active Models optimization with Differential Evolution
Expert Systems with Applications: An International Journal
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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.