Towards distortion-free imaging of the eye

Substrip-based registration and automatic montaging of adaptive optics retinal images

Precise registration and montage are critical for high-resolution adaptive optics retinal image analysis but are challenged by rapid eye movement. We present a substrip-based method to improve image registration and facilitate the automatic montaging of adaptive optics scanning laser ophthalmoscopy (AOSLO). The program first batches the consecutive images into groups based on a translation threshold and selects an image with minimal distortion within each group as the reference. Within each group, the software divides each image into multiple strips and calculates the Normalized Cross-Correlation with the reference frame using two substrips at both ends of the whole strip to estimate the strip translation, producing a registered image. Then, the software aligns the registered images of all groups also using a substrip based registration, thereby generating a montage with cell-for-cell precision in the overlapping areas of adjacent frames. The algorithm was evaluated with AOSLO images acquired in human subjects with normal macular health and patients with age-related macular degeneration (AMD). Images with a motion amplitude of up to 448 pixels in the fast scanner direction over a frame of 512 × 512 pixels can be precisely registered. Automatic montage spanning up to 22.6 degrees on the retina was achieved on a cell-to-cell precision with a low misplacement rate of 0.07% (11/16,501 frames) in normal eyes and 0.51% (149/29,051 frames) in eyes with AMD. Substrip based registration significantly improved AOSLO registration accuracy.

Evolution of adaptive optics retinal imaging [Invited]

This review describes the progress that has been achieved since adaptive optics (AO) was incorporated into the ophthalmoscope a quarter of a century ago, transforming our ability to image the retina at a cellular spatial scale inside the living eye. The review starts with a comprehensive tabulation of AO papers in the field and then describes the technological advances that have occurred, notably through combining AO with other imaging modalities including confocal, fluorescence, phase contrast, and optical coherence tomography. These advances have made possible many scientific discoveries from the first maps of the topography of the trichromatic cone mosaic to exquisitely sensitive measures of optical and structural changes in photoreceptors in response to light. The future evolution of this technology is poised to offer an increasing array of tools to measure and monitor in vivo retinal structure and function with improved resolution and control.

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

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 (512×512 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.