Evolutionary learning of spiking neural networks towards quantification of 3D MRI brain tumor tissues

Verfasser / Beitragende:
[Arunadevi Baladhandapani, Deepa Nachimuthu]
Ort, Verlag, Jahr:
2015
Enthalten in:
Soft Computing, 19/7(2015-07-01), 1803-1816
Format:
Artikel (online)
ID: 605469113
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024 7 0 |a 10.1007/s00500-014-1364-z  |2 doi 
035 |a (NATIONALLICENCE)springer-10.1007/s00500-014-1364-z 
245 0 0 |a Evolutionary learning of spiking neural networks towards quantification of 3D MRI brain tumor tissues  |h [Elektronische Daten]  |c [Arunadevi Baladhandapani, Deepa Nachimuthu] 
520 3 |a 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. 
540 |a Springer-Verlag Berlin Heidelberg, 2014 
690 7 |a 3D Magnetic resonance imaging  |2 nationallicence 
690 7 |a Multi-dimensional co-occurrence matrices  |2 nationallicence 
690 7 |a Spiking neural networks  |2 nationallicence 
690 7 |a Izhikevich neurons  |2 nationallicence 
690 7 |a Genetic algorithm  |2 nationallicence 
700 1 |a Baladhandapani  |D Arunadevi  |u Department of EEE, Anna University-Regional Centre, Jothipuram, 641047, Coimbatore, India  |4 aut 
700 1 |a Nachimuthu  |D Deepa  |u Department of EEE, Anna University-Regional Centre, Jothipuram, 641047, Coimbatore, India  |4 aut 
773 0 |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/7(2015-07-01), 1803-1816  |x 1432-7643  |q 19:7<1803  |1 2015  |2 19  |o 500 
856 4 0 |u https://doi.org/10.1007/s00500-014-1364-z  |q text/html  |z Onlinezugriff via DOI 
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900 7 |a Metadata rights reserved  |b Springer special CC-BY-NC licence  |2 nationallicence 
908 |D 1  |a research-article  |2 jats 
949 |B NATIONALLICENCE  |F NATIONALLICENCE  |b NL-springer 
950 |B NATIONALLICENCE  |P 856  |E 40  |u https://doi.org/10.1007/s00500-014-1364-z  |q text/html  |z Onlinezugriff via DOI 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Baladhandapani  |D Arunadevi  |u Department of EEE, Anna University-Regional Centre, Jothipuram, 641047, Coimbatore, India  |4 aut 
950 |B NATIONALLICENCE  |P 700  |E 1-  |a Nachimuthu  |D Deepa  |u Department of EEE, Anna University-Regional Centre, Jothipuram, 641047, Coimbatore, India  |4 aut 
950 |B NATIONALLICENCE  |P 773  |E 0-  |t Soft Computing  |d Springer Berlin Heidelberg  |g 19/7(2015-07-01), 1803-1816  |x 1432-7643  |q 19:7<1803  |1 2015  |2 19  |o 500