Angiogram, Fundus, and Oxygen Saturation Optic Nerve Head Image Fusion

摘要

A novel multi-modality optic nerve head image fusion approach has been successfully designed. The new approach has been applied on three ophthalmologic modalities: angiogram, fundus, and oxygen saturation retinal optic nerve head images. It has achieved an excellent result by giving the visualization of fundus or oxygen saturation images with a complete angiogram overlay. During this study, two contributions have been made in terms of novelty, efficiency, and accuracy. The first contribution is the automated control point detection algorithm for multi-sensor images. The new method employs retina vasculature and bifurcation features by identifying the initial good-guess of control points using the Adaptive Exploratory Algorithm. The second contribution is the heuristic optimization fusion algorithm. In order to maximize the objective function (Mutual-Pixel-Count), the iteration algorithm adjusts the initial guess of the control points at the sub-pixel level. A refinement of the parameter set is obtained at the end of each loop, and finally an optimal fused image is generated at the end of the iteration. It is the first time that Mutual-Pixel-Count concept has been introduced into biomedical image fusion area. By locking the images in one place, the fused image allows ophthalmologists to match the same eye over time and get a sense of disease progress and pinpoint surgical tools. The new algorithm can be easily expanded to human or animals' 3D eye, brain, or body image registration and fusion.