caa a22 4500 605469113 CHVBK 20210128100320.0 cr unu---uuuuu 210128e20150701xx s 000 0 eng 10.1007/s00500-014-1364-z doi (NATIONALLICENCE)springer-10.1007/s00500-014-1364-z Evolutionary learning of spiking neural networks towards quantification of 3D MRI brain tumor tissues [Elektronische Daten] [Arunadevi Baladhandapani, Deepa Nachimuthu] This paper presents a new classification technique for 3D MR images, based on a third-generation network of spiking neurons. Implementation of multi-dimensional co-occurrence matrices for the identification of pathological tumor tissue and normal brain tissue features are assessed. The results show the ability of spiking classifier with iterative training using genetic algorithm to automatically and simultaneously recover tissue-specific structural patterns and achieve segmentation of tumor part. The spiking network classifier has been validated and tested for various real-time and Harvard benchmark datasets, where appreciable performance in terms of mean square error, accuracy and computational time is obtained. The spiking network employed Izhikevich neurons as nodes in a multi-layered structure. The classifier has been compared with computational power of multi-layer neural networks with sigmoidal neurons. The results on misclassified tumors are analyzed and suggestions for future work are discussed. Springer-Verlag Berlin Heidelberg, 2014 3D Magnetic resonance imaging nationallicence Multi-dimensional co-occurrence matrices nationallicence Spiking neural networks nationallicence Izhikevich neurons nationallicence Genetic algorithm nationallicence Baladhandapani Arunadevi Department of EEE, Anna University-Regional Centre, Jothipuram, 641047, Coimbatore, India aut Nachimuthu Deepa Department of EEE, Anna University-Regional Centre, Jothipuram, 641047, Coimbatore, India aut Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1803-1816 1432-7643 19:7<1803 2015 19 500 https://doi.org/10.1007/s00500-014-1364-z text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1364-z text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Baladhandapani Arunadevi Department of EEE, Anna University-Regional Centre, Jothipuram, 641047, Coimbatore, India aut NATIONALLICENCE 700 1- Nachimuthu Deepa Department of EEE, Anna University-Regional Centre, Jothipuram, 641047, Coimbatore, India aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/7(2015-07-01), 1803-1816 1432-7643 19:7<1803 2015 19 500