Polynomial transformation model for frame-to-frame registration in an adaptive optics confocal scanning laser ophthalmoscope.

Abstract

The adaptive optics (AO) technique has been integrated in confocal scanning laser ophthalmoscopy (SLO) to obtain near diffraction-limited high-resolution retinal images. However, the quality of AOSLO images is decreased by various sources of noise and fixational eye movements. To improve image quality and remove distortions in AOSLO images, the multi-frame averaging method is usually utilized, which relies on an accurate image registration. The goal of image registrations is finding the optimal transformation to best align the input image sequences. However, current methods for AOSLO image registration have some obvious defects due to the limitation of transformation models. In this paper, we first established the retina motion model by using the Taylor series and polynomial expansion. Then we generated the polynomial transformation model and provided its close-form solution for consecutively frame-to-frame AOSLO retina image registration, allowing one to consider more general retinal motions such as scale changes, shearing and rotation motions, and so on. The experimental results demonstrated that higher-order polynomial transformation models are helpful to achieve more accurate registration, and the fourth-order polynomial transformation model is preferred to accomplish an efficient registration with a satisfying computational complexity. In addition, the AKAZE feature detection method was adopted and improved to achieve more accurate image registrations, and a new strategy was validated to exclude those unsuccessful registered regions to promote the robustness of image registration.