光学学报, 2020, 40 (10): 1011002, 网络出版: 2020-04-28
基于粒子群优化算法的光学相干层析像差校正方法 下载: 1220次
An Optical Coherence Tomographic Aberration Correction Method Based on the Particle Swarm Optimization Algorithm
成像系统 生物医学成像 光学相干层析 像差校正 泽尼克多项式 粒子群优化 imaging systems medical and biological imaging optical coherence tomography aberration correction Zernike polynomials particle swarm optimization
摘要
光学相干层析成像系统在扫描成像时,会不可避免地引入附加像差。此时,图像细节信息丢失,无法满足医学成像的高清晰度要求。为此,提出一种基于粒子群优化算法的像差校正方法。将像差校正过程以滤波形式建模,由泽尼克多项式的线性组合构成滤波器,通过选定图像信息熵或图像清晰度作为优化指标,利用粒子群优化算法进行迭代估计多项式的最佳系数值,最终得到清晰图像。以分辨率板为仿真目标图像分别加载离焦及低阶混合波前像差,以图像信息熵和清晰度分别作为评价函数,复原结果误差均方根误差(RMS)值均小于0.1λ,得以清晰成像;实验采集洋葱细胞图像,以信息熵作为评价指标,校正像差后其下降18%;采集葡萄组织图像,以清晰度作为评价指标,校正像差后其上升36%;细胞和组织轮廓信息均得以分辨。
Abstract
An optical coherence tomography system will inevitably introduce additional aberration into scanning imaging. Thus, image details are lost, and the high definition requirements of medical imaging cannot be satisfied. In this study, we proposed an aberration correction method based on the particle swarm optimization algorithm. The aberration correction method was modeled as a filtering process based on a linear combination of the Zernike polynomials. The particle swarm optimization algorithm was used to iteratively estimate the optimal coefficient value of the polynomials by considering the image information entropy or sharpness as the optimization index. Further, the resolution plate was used as the simulation target image to load the defocused and low-order mixed wavefront aberrations. The image information entropy and sharpness were considered to be the evaluation functions. The root mean square error values of the restoration results were less than 0.1λ, so the clear imaging can be obtained. For the experimentally collected onion cells, the information entropy was considered to be the evaluation index, which decreased by 18% after aberration correction. However, for the collected grape tissue image, sharpness was considered to be the evaluation index, which increased by 36% after aberration correction.
毕津慈, 高志山, 朱丹, 马剑秋, 袁群, 郭珍艳, 屈艺, 殷长俊, 徐尧. 基于粒子群优化算法的光学相干层析像差校正方法[J]. 光学学报, 2020, 40(10): 1011002. Jinci Bi, Zhishan Gao, Dan Zhu, Jianqiu Ma, Qun Yuan, Zhenyan Guo, Yi Qu, Changjun Yin, Yao Xu. An Optical Coherence Tomographic Aberration Correction Method Based on the Particle Swarm Optimization Algorithm[J]. Acta Optica Sinica, 2020, 40(10): 1011002.