扫频光学相干层析视网膜图像配准去噪算法

Speckle noise reduction in swept-source optical coherence tomography by retinal image registration

多帧叠加平均处理是去除扫频光学相干层析系统散斑噪声、获得较为清晰结构信息的有效方法,但眼睛的震颤、漂移、微眼跳等生理特性和系统光路特性会使图像之间存在错位,导致叠加效果不佳、结构稳定性差,为此本文提出一种基于灰度分布信息和目标几何信息相结合的配准算法。该方法根据图像平均灰度分布提取包含目标信息的感兴趣区域,通过相位相关算法和基于分段拟合的灰度投影算法的双重作用校正图像的平移变换;通过拟合视网膜上边界作为特征点迭代确定最佳旋转参数,并再次重新估计平移参数,实现图像的刚性配准;最后通过轴向扫描一对一映射法以能量函数为约束条件实现图像的非刚性配准。对活体兔眼进行实验,结果表明,本文算法配准后的叠加图像边界清晰,结构信息增强,信噪比和对比度平均有效提高一倍多。本算法适用于强噪声视网膜B-Scans图像的配准,能满足多种类型OCT系统的叠加成像需要,具有较高的鲁棒性和图像配准精度。

The averaging of multiple B-Scans is an effective method of reducing speckle noise in Swept-Source Optical Coherence Tomography(SS-OCT)and obtaining clear structural information.However,physiological characteristics such as eye tremor,drift,micro-saccade,and the optical structure of an SS-OCT system cause geometric transformation between images,resulting in poor multi-frame averaging.In this paper,we propose a registration algorithm based on the combination of gray distribution information and target geometric information.This method extracts the region of interest containing target information using the average gray distribution of an image,and corrects the transformation of the image with the collective effect of the phase correlation algorithm and the gray projection algorithm based on the fitting of the curve of its segments.Then,the process is repeated with the upper boundary of the retinal image fitted as the feature points to determine the optimal rotation parameters.The translation parameters are re-estimated again to achieve the rigid registration of the image.Finally,a one-to-one mapping method of axial scanning is used to achieve the non-rigid registration of the image with the energy function as the constraint.Experiments on live rabbit eyes show that the averaged image has clear boundaries,enhanced structural information,and its signal-to-noise and contrast-to-noise ratios are more than doubled their previous values on average.The algorithm is suitable for the registration of B-Scan images with strong speckle noise and can meet the averaging needs of many types of OCT systems.It has high robustness and image registration accuracy.