Automatic hippocampus localization in histological images using PSO-based deformable models

Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication

Volumn , Issue , 2011, Pages 487-494

  Ugolotti, Roberto ^a   Mesejo, Pablo ^a   Cagnoni, Stefano ^a   Giacobini, Mario ^b   Di Cunto, Ferdinando ^b  

^a UNIVERSITY OF PARMA   (Italy)

^b UNIVERSITY OF TURIN   (Italy)

Author keywords

active shape models; affine registration; allen brain atlas; automatic localization; hippocampus; particle swarm optimization

Indexed keywords

ACTIVE SHAPE MODELS; AFFINE REGISTRATION; ALLEN BRAIN ATLAS; AUTOMATIC LOCALIZATION; HIPPOCAMPUS; PARTICLE SWARM;

BRAIN MODELS; DEFORMATION; GENE EXPRESSION; MAMMALS;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 80051932750     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2001858.2002038     Document Type: Conference Paper

References (23)

1. Allen Institute for Brain Science. Allen Reference Atlases. http://mouse.brain-map.org, 2004-2006.
2. L. Ballerini. Genetic snakes for color images segmentation. In Applications of Evolutionary Computing, volume 2037 of Lecture Notes in Computer Science, pages 268-277. Springer Berlin / Heidelberg, 2001.
3. A. Banks, J. Vincent, and C. Anyakoha. A review of Particle Swarm Optimization. Part I: background and development. Natural Computing, 6:467-484, 2007.
4. J. Barnes, J. W. Bartlett, L. A. van de Pol, C. T. Loy, R. I. Scahill, C. Frost, P. Thompson, and N. C. Fox. A meta-analysis of hippocampal atrophy rates in Alzheimer's disease. Neurobiology of Aging, 30(11):1711-1723, 2009.
5. O. T. Carmichael, H. A. Aizenstein, S. W. Davis, J. T. Becker, P. M. Thompson, C. C. Meltzer, and Y. Liu. Atlas-based hippocampus segmentation in Alzheimer's disease and mild cognitive impairment. NeuroImage, 27:979-990, 2005. (Pubitemid 41317265)
6. M. Clerc. Stagnation analysis in Particle Swarm Optimization or what happens when nothing happens. Technical Report CSM-460, Department of Computer Science, University of Essex, 2006. Edited by Riccardo Poli.
7. T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham. Active shape models-their training and application. Comput. Vis. Image Underst., 61:38-59, 1995.
8. O. Cordón, S. Damas, and J. Santamaría. A fast and accurate approach for 3D image registration using the scatter search evolutionary algorithm. Pattern Recognition Letters, 27(11):1191-1200, 2006.
9. S. Gefen, N. Kiryati, and J. Nissanov. Atlas-based indexing of brain sections via 2-D to 3-D image registration. IEEE Transactions on Biomedical Engineering, 55(1):147-156, 2008. (Pubitemid 350308412)
10. A. Ghanei, H. Soltanian-Zadeh, and J. Windham. A deformable model for hippocampus segmentation: improvements and extension to 3D. In IEEE Nuclear Science Symposium, volume 3, pages 1797-1801, 1996.
11. J. Kennedy and R. Eberhart. Particle Swarm Optimization. In Proceedings of IEEE International Conference on Neural Networks, volume 4, pages 1942-1948, 1995.
12. B. Liu, L. Wang, Y.-H. Jin, F. Tang, and D.-X. Huang. Improved Particle Swarm Optimization combined with chaos. Chaos, Solitons & Fractals, 25(5):1261-1271, 2005.
13. T. McInerney and D. Terzopoulos. Deformable models in medical image analysis: a survey. Medical Image Analysis, 1(2):91-108, 1996. (Pubitemid 126421958)
14. C. McIntosh and G. Hamarneh. Evolutionary deformable models for medical image segmentation: A genetic algorithm approach to optimizing learned, intuitive, and localized medial-based shape deformation. In Genetic and Evolutionary Computation: Medical Applications, pages 46-67. John Wiley & Sons Ltd, 2010.
15. L. Mussi, S. Cagnoni, E. Cardarelli, F. Daolio, P. Medici, and P. Porta. GPU implementation of a road sign detector based on particle swarm optimization. Evolutionary Intelligence, 3:155-169, 2010.
16. K. A. Norman. How hippocampus and cortex contribute to recognition memory: revisiting the complementary learning systems model. Hippocampus, 20(11):1217-1227, 2010.
17. A. Osokin, D. Vetrov, and D. Kropotov. 3-D Mouse Brain Model Reconstruction from a Sequence of 2-D Slices in Application to Allen Brain Atlas. In Computational Intelligence Methods for Bioinformatics and Biostatistics, volume 6160 of Lecture Notes in Computer Science, pages 291-303. Springer Berlin / Heidelberg, 2010.
18. R. Poli. Analysis of the publications on the applications of particle swarm optimisation. J. Artificial Evolution and Applications, pages 1-10, 2008.
19. T. Riklin-Raviv, N. Sochen, N. Kiryati, N. Ben-Zadok, S. Gefen, L. Bertand, and J. Nissanov. Propagating distributions for segmentation of brain atlas. In 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2007 (ISBI'07), pages 1304-1307, 2007.
20. Y. Shi and R. Eberhart. Empirical study of Particle Swarm Optimization. In Proc. Congress on Evolutionary Computation (CEC'99), volume 3, pages 1945-1950, 1999.
21. F. van der Lijn, T. den Heijer, M. M. Breteler, and W. J. Niessen. Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts. Neuroimage, 43:708-720, 2008.
22. P. Yushkevich, B. Avants, L. Ng, M. Hawrylycz, P. Burstein, H. Zhang, and J. Gee. 3D mouse brain reconstruction from histology using a coarse-to-fine approach. In Biomedical Image Registration, volume 4057 of Lecture Notes in Computer Science, pages 230-237. Springer Berlin / Heidelberg, 2006.
23. B. Zitová and J. Flusser. Image registration methods: a survey. Image and Vision Computing, 21:977-1000, 2003.