A CNN based algorithm for the automated segmentation of multiple sclerosis lesions

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6024 LNCS, Issue PART 1, 2010, Pages 211-220

  Bilotta, Eleonora ^a   Cerasa, Antonio ^b   Pantano, Pietro ^a   Quattrone, Aldo ^b   Staino, Andrea ^a   Stramandinoli, Francesca ^a  

^a UNIVERSITY OF CALABRIA   (Italy)

^b INSTITUTE OF NEUROLOGICAL SCIENCES   (Italy)

Author keywords

Automated Magnetic Resonance Imaging Analysis; Cellular Neural Networks; Genetic Algorithms; Multiple Sclerosis lesion load

Indexed keywords

BRAIN; DIAGNOSIS; GENETIC ALGORITHMS; MAGNETIC RESONANCE IMAGING;

AUTOMATED MAGNETIC RESONANCE IMAGING ANALYSIS; AUTOMATED SEGMENTATION; BRAIN TISSUE; GENETIC ALGORITHM (GAS); MAGNETIC RESONANCE IMAGES (MRI); MULTIPLE SCLEROSIS; MULTIPLE SCLEROSIS LESIONS; NEW APPLICATIONS;

CELLULAR NEURAL NETWORKS;

EID: 77952348474     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-12239-2_22     Document Type: Conference Paper

References (10)

1. Bilotta, E., Pantano, P.: Cellular Non-Linear Networks as a New Paradigm for Evolutionary Robotics. In: Iba, H. (ed.) Frontiers in Evolutionary Robotics, Vienna, Austria, pp. 87-108 (2008)
2. Chua, L.O., Roska, T.: Cellular Neural Networks and Visual Computing: Foundations and Applications. Cambridge University Press, Cambridge (2004)
3. Chua, L.O., Yang, L.: Cellular Neural Networks: Theory. IEEE Transaction on Circuits and Systems 35(10), 1257-1272 (1988)
4. Dice, L.R.: Measures of the amount of ecologic association between species. Ecology 26, 297-302 (1945)
5. Döhler, F., Mormann, F., Weber, B., Elger, C.E., Lehnertz, K.: A Cellular Neural Network based Method for Classification of Magnetic Resonance Images: Towards an Automated Detection of Hippocampal Sclerosis. In: Proceedings of the 7th IEEE International Workshop on Cellular Neural Networks and their Applications, pp. 579-586 (2004)
6. Kek, L., Karacs, K., Roska, T.: Cellular Wave Computing Library (Templates, Algorithms and Programs), ver. 2.1. Cellular SensoryWave Computers Laboratory, Hungarian Academy of Sciences (2007)
7. SPM8 - Statistical Parametric Mapping, http://www.fil.ion.ucl.ac.uk/spm/ software/spm8/
8. Szabo, T., Barsi, P., Szolgay, P.: Application of Analogic CNN algorithms in Telemedical Neuroradiology. Journal of Neuroscience Methods 170(7), 2063-2090 (2005)
9. Valentino, P., Cerasa, A., Chiriaco, C., Nistic̀o, R., Pirritano, D., Gioia, M., Lanza, P., Canino, M., Del Giudice, F., Gallo, O., Condino, F., Torchia, G., Quattrone, A.: Cognitive deficits in multiple sclerosis patients with cerebellar symptoms. Multiple Sclerosis 15, 854-859 (2009)
10. Völk, K., Miller, J.F., Smith, S.L.: Multiple Network CGP for the Classification of Mammograms. In: Giacobini, M., Brabazon, A., Cagnoni, S., Caro, G.A.d., Ekart, A., Esparcia-Alćazar, A.I., Farooq, M., Fink, A., Machado, P., McCormack, J., O'Neill, M., Neri, F., Preus, M., Rothlauf, F., Tarantino, E., Yang, S. (eds.) EvoWorkshops 2009. LNCS, vol.5484, pp. 405-413. Springer, Heidelberg (2009)