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Application of Fractal and Grey Level Co-Occurrence Matrix Analysis in Evaluation of Brain Corpus Callosum and Cingulum Architecture

Published online by Cambridge University Press:  26 June 2014

Igor Pantic Open the ORCID record for Igor Pantic [Opens in a new window] ,
Sanja Dacic ,
Predrag Brkic ,
Irena Lavrnja ,
Senka Pantic ,
Tomislav Jovanovic  and
Sanja Pekovic
Igor Pantic*
Affiliation:
Institute of Medical Physiology, School of Medicine, University of Belgrade, Visegradska 26/II, 11129, Belgrade, Serbia
Sanja Dacic
Affiliation:
Institute of Physiology and Biochemistry, Faculty of Biology, University of Belgrade, Studentski trg 3, 11000, Belgrade, Serbia
Predrag Brkic
Affiliation:
Institute of Medical Physiology, School of Medicine, University of Belgrade, Visegradska 26/II, 11129, Belgrade, Serbia
Irena Lavrnja
Affiliation:
Department of Neurobiology, Institute for Biological Research “Sinisa Stankovic”, University of Belgrade, Boulevard Despot Stefan 142, 11060 Belgrade, Serbia
Senka Pantic
Affiliation:
Institute of Histology, School of Medicine, University of Belgrade, Visegradska 26/II, 11129, Belgrade, Serbia
Tomislav Jovanovic
Affiliation:
Institute of Medical Physiology, School of Medicine, University of Belgrade, Visegradska 26/II, 11129, Belgrade, Serbia
Sanja Pekovic
Affiliation:
Department of Neurobiology, Institute for Biological Research “Sinisa Stankovic”, University of Belgrade, Boulevard Despot Stefan 142, 11060 Belgrade, Serbia
*
*Corresponding author. [email protected]
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Abstract

This aim of this study was to assess the discriminatory value of fractal and grey level co-occurrence matrix (GLCM) analysis methods in standard microscopy analysis of two histologically similar brain white mass regions that have different nerve fiber orientation. A total of 160 digital micrographs of thionine-stained rat brain white mass were acquired using a Pro-MicroScan DEM-200 instrument. Eighty micrographs from the anterior corpus callosum and eighty from the anterior cingulum areas of the brain were analyzed. The micrographs were evaluated using the National Institutes of Health ImageJ software and its plugins. For each micrograph, seven parameters were calculated: angular second moment, inverse difference moment, GLCM contrast, GLCM correlation, GLCM variance, fractal dimension, and lacunarity. Using the Receiver operating characteristic analysis, the highest discriminatory value was determined for inverse difference moment (IDM) (area under the receiver operating characteristic (ROC) curve equaled 0.925, and for the criterion IDM≤0.610 the sensitivity and specificity were 82.5 and 87.5%, respectively). Most of the other parameters also showed good sensitivity and specificity. The results indicate that GLCM and fractal analysis methods, when applied together in brain histology analysis, are highly capable of discriminating white mass structures that have different axonal orientation.

Keywords

axondirectionalitytexturesensitivitydiscriminatory value
Type
Biological Applications
Information
Microscopy and Microanalysis , Volume 20 , Issue 5 , October 2014 , pp. 1373 - 1381
Copyright
© Microscopy Society of America 2014 

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