| Autor: |
Sathiya K. G., Srinivasan, S., Sivakumaran, T. S. |
| Předmět: |
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| Zdroj: |
Medico-Legal Update; Jan-Jun2018, Vol. 18 Issue 1, p555-561, 7p |
| Abstrakt: |
Glaucoma is a condition that damages optic nerve head which is irreversible if it is not treated at the earliest. In this paper, Optical Coherence Tomography (OCT) image classification for glaucoma diagnosis is presented which uses texture statistical approach for classification. A set of common statistical features from the OCT image and another set of statistical features from the Gray Level Difference Matrix (GLDM) of OCT image are used. They are analyzed independently by a supervised classifier named Support Vector Machine (SVM). To obtain higher accuracy, two sets of features are combined linearly and tested. Experimental results show that the OCT image classification system provides an accuracy of 95.5% with sensitivity of 94% and specificity of 97% by the combination of features. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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