Automatic Hippocampus Localization in Histological Images using Differential Evolution-Based Deformable

Pablo Mesejo 1 Roberto Ugolotti 1 Ferdinando Di Cunto 2 Mario Giacobini 2, 3 Stefano Cagnoni 1
1 Intelligent Bio-Inspired Systems lab (IBISlab)
2 Molecular Biotechnology Center
3 Department of Veterinary Sciences
Abstract : In this paper, the localization of structures in biomedical images is considered as a multimodal global continuous optimization problem and solved by means of soft computing techniques. We have developed an automatic method aimed at localizing the hippocampus in histological images, after discoveries indicating the relevance of structural changes of this region as early biomarkers for Alzheimer’s disease and epilepsy. The localization is achieved by searching the parameters of an empirically-derived deformable model of the hippocampus which maximize its overlap with the corresponding anatomical structure in histological brain images. The comparison between six real-parameter optimization techniques (Levenberg–Marquardt, Differential Evolution, Simulated Annealing, Genetic Algorithms, Particle Swarm Optimization and Scatter Search) shows that Differential Evolution significantly outperforms the other techniques in this task, providing successful localizations in 90.9% and 93.0% of two test sets of real and synthetic images, respectively.
Keywords : Particle Swarm Optimization Scatter Search Global Continuous Optimization Hippocampus Localization Deformable Models Genetic Algorithms Levenberg–Marquardt Differential Evolution Simulated Annealing
Type de document :
Article dans une revue
Pattern Recognition Letters, Elsevier, 2012, 34 (3), pp.299-307
Liste complète des métadonnées

Littérature citée [4 références]  Voir  Masquer  Télécharger
https://hal.inria.fr/hal-01221303
Contributeur : Pablo Mesejo Santiago <>
Soumis le : mardi 27 octobre 2015 - 16:45:44
Dernière modification le : mardi 10 novembre 2015 - 23:38:32
Document(s) archivé(s) le : jeudi 28 janvier 2016 - 11:14:09

Fichier

paperPRL_review2.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : hal-01221303, version 1

Collections

Citation

Pablo Mesejo, Roberto Ugolotti, Ferdinando Di Cunto, Mario Giacobini, Stefano Cagnoni. Automatic Hippocampus Localization in Histological Images using Differential Evolution-Based Deformable. Pattern Recognition Letters, Elsevier, 2012, 34 (3), pp.299-307. 〈hal-01221303〉

Exporter

BibTeX TEI DC DCterms EndNote

Partager

Métriques

Consultations de la notice

88

Téléchargements de fichiers

39

Contact


archive-ouverte@inria.fr