Feature extraction and classification for pupillary images of rats

Kalmár, György and Büki, Alexandra and Kékesi, Gabriella and Horváth, Gyöngyi and Nyúl, László G.: Feature extraction and classification for pupillary images of rats. Conference of PhD Students in Computer Science, (11). pp. 88-91. (2018)

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Abstract

The investigation of the pupillary light reflex (PLR) is a well-known method to provide information about the functionality of the autonomic nervous system. Pupillometry, a non-invasive technique, was applied in our lab to study the schizophrenia-related PLR alterations in a new selectively bred rat substrain, named WISKET. The pupil responses to light impulses were recorded with an infrared camera; the videos were automatically processed and features were extracted. Besides the classical statistical analysis (ANOVA), feature selection and classification were applied to reveal the significant differences in the PLR parameters between the control and WISKET animals.

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