Computerized mouse pupil size measurement for pupillary light reflex analysis

Abstract

Accurate measurement of pupil size is essential for pupillary light reflex (PLR) analysis in clinical diagnosis and vision research. Low pupil–iris contrast, corneal reflection, artifacts and noises in infrared eye imaging pose challenges for automated pupil detection and measurement. This paper describes a computerized method for pupil detection or identification. After segmentation by a region-growing algorithm, pupils are detected by an iterative randomized Hough transform (IRHT) with an elliptical model. The IRHT iteratively suppresses the effects of extraneous structures and noise, yielding reliable measurements. Experimental results with 72 images showed a mean absolute difference of 3.84% between computerized and manual measurements. The inter-run variation for the computerized method (1.24%) was much smaller than the inter-observer variation for the manual method (7.45%), suggesting a higher level of consistency of the former. The computerized method could facilitate PLR analysis and other non-invasive functional tests that require pupil size measurements.