Abbasi Nima, Chen Keyu, Wong Alexander, Bizheva Kostadinka
Department of Systems Design Engineering, University of Waterloo, Waterloo, Ontario, Canada.
Department of Physics and Astronomy, University of Waterloo, Waterloo, Ontario, Canada.
Biomed Opt Express. 2024 Aug 23;15(9):5491-5504. doi: 10.1364/BOE.530569. eCollection 2024 Sep 1.
The trade-off between transverse resolution and depth-of-focus (DOF) typical for optical coherence tomography (OCT) systems based on conventional optics, prevents "single-shot" acquisition of volumetric OCT images with sustained high transverse resolution over the entire imaging depth. Computational approaches for correcting defocus and higher order aberrations in OCT images developed in the past require highly stable phase data, which poses a significant technological challenge. Here, we present an alternative computational approach to sharpening OCT images and reducing speckle noise, based on intensity OCT data. The novel algorithm uses non-local priors to model correlated speckle noise within a maximum framework to generate sharp and noise-free images. The performance of the algorithm was tested on images of plant tissue (cucumber) and healthy human cornea, acquired with line-field spectral domain OCT (LF-SD-OCT) systems. The novel algorithm effectively suppressed speckle noise and sharpened or recovered morphological features in the OCT images for depths up to 13×DOF (depth-of-focus) relative to the focal plane.
基于传统光学的光学相干断层扫描（OCT）系统中典型的横向分辨率与焦深（DOF）之间的权衡，阻碍了在整个成像深度上以持续的高横向分辨率“单次”采集体积OCT图像。过去开发的用于校正OCT图像中散焦和高阶像差的计算方法需要高度稳定的相位数据，这带来了重大的技术挑战。在此，我们提出了一种基于强度OCT数据的用于锐化OCT图像和减少散斑噪声的替代计算方法。该新算法使用非局部先验在最大框架内对相关散斑噪声进行建模，以生成清晰且无噪声的图像。该算法的性能在通过线场光谱域OCT（LF-SD-OCT）系统采集的植物组织（黄瓜）和健康人角膜的图像上进行了测试。相对于焦平面，该新算法有效地抑制了散斑噪声，并锐化或恢复了深度达13×DOF（焦深）的OCT图像中的形态特征。
