仿鹰视顶盖的眼底OCT图像重建方法

Reconstruction Method of Eye OCT Image Imitating Eagle Optic Tectum

客观因素导致临床获得的眼底OCT图像存在对比度差、病灶区域边缘模糊等现象.为解决上述问题,借鉴鹰视觉系统的信息处理机制,提出单幅OCT图像的超分辨率重建方法EOTRN.它仿照鹰眼视顶盖逐步扩大感受野的思路,从纵、横两维度逐级挖掘高级语义特征.纵向维度上借助空洞卷积、密集连接、通道注意力实现感受野逐步扩大、不同网络层特征传播及不同通道特征间的“竞争”与“合作”,完成低频信号的高级语义特征的初步提取.横向维度上借助64个特征子空间剔除高级语义特征中的冗余信息,校正并突出显著信息,实现病灶区域的纹理、轮廓特征强化.最后对底层语义特征和高级语义特征进行上采样和深层重建,得到高清OCT图像.仿真表明,在×4放大倍数时,EOTRN对测试集3的PSNR和SSIM值比EMASRN分别提高了0.96%和1.36%,重建图像能够突出细节信息,真实反映眼底健康状况.EOTRN的参数量较少,适用于嵌入式系统的部署,实现眼底OCT图像的实时超清重建.

Objective factors lead to poor contrast and blurred edges of the lesion area in eye optical coherence tomography(OCT)images obtained clinically.To address these issues,a super-resolution reconstruction method for single eye OCT image,named EOTRN,is proposed by referring to the information processing mechanism of the eagle vision system.It imitates the idea of gradually expanding the receptive field of the eagle optic tectum,and excavates advanced semantic features from both the vertical and horizontal dimensions step by step.In the vertical dimension,EOTRN utilizes dilated convolutions,dense connection and a channel attention mechanism to gradually expand the receptive field.This process propagates the characteristics of different network layers,enabling competition or cooperation among different channel features.As a result,the preliminary extraction of advanced semantic features of low-frequency signals is achieved.In the horizontal dimension,EOTRN eliminates redundant information from the advanced semantic features,corrects and highlights salient information,and enhances the texture and contour features of the lesion areas using 64 characteristic subspaces.Finally,the underlying semantic features and the advanced semantic features are upsampled and deeply reconstructed to obtain high-definition images.the Experiments show that,for the third test set with scale factor×4,compared with EMASRN,EOTRN achieves 0.96%increase in PSNR and 1.36%increase in SSIM values.The reconstructed images generated by EOTRN effectively highlight the detailed information and accurately reflect the health of the fundus.Moreover,EOTRN has fewer parameters,making it suitable for the deployment of embedded systems to realize real-time ultra-clear reconstruction of eye OCT images.