Real-time correction of image rotation with adaptive optics scanning light ophthalmoscopy

Abstract

Fixational eye motion includes typical translation and torsion. In the registration of images from adaptive optics scanning light ophthalmoscopy (AOSLO), image rotation due to eye torsion and/or head rotation is often ignored because (a) the amount of rotation is trivial compared to translation within a short duration of imaging or recording time and (b) computational cost increases substantially when the registration algorithm involves simultaneous detection of rotation and translation. However, it becomes critically important under cases such as long exposure, functional measurements, and precise motion tracking. We developed a fast method to detect and correct rotation from AOSLO images, together with the detection of strip-level motion translation. The computational cost for rotation detection and correction alone is about 5 ms/frame ( $512\times 512$ pixels) on an nVidia GTX960M GPU. Image quality is compared with and without rotation correction from 10 healthy human subjects and 8 diseased eyes with a total of 180 videos. The results show that residual image motions between the reference images and the registered images with rotation correction are a fraction of those without rotation correction, and the ratio is 0.74–0.89 at the image center and 0.37–0.51 at the four corners of the images.