论文标题

直接3D信息融合,用于光学声学显微镜中磁场深度增强的深度增强

Direct 3D information fusion for depth of field enhancement in optical-resolution photoacoustic microscopy

论文作者

Song, Xianlin, Li, Sihang, Wang, Zhuangzhuang

论文摘要

作为光声显微镜的重要分支,光学分辨率光学显微镜由于强烈的激光束而受到有限的景深。在这项工作中,提出了基于3D固定小波变换和关节加权评估优化的3D信息融合算法,以融合多对焦光声数据,以实现大量和高分辨率的3D成像。首先,在多对焦数据上进行了三维固定小波变换,以获得八个小波系数。然后,使用基于关节加权评估的差异进化算法来优化每个小波系数的分裂块大小。多聚焦3D数据的相应亚漏洞与使用标准偏差进行焦点检测的建议融合规则融合在一起。最后,通过在8个融合的亚曲线剂上施加反向固定小波变换,可以实现具有较大景深的光声显微镜。多聚焦纤维纤维的融合结果表明,光学分辨率光声显微镜的景深无需通过提出的方法牺牲横向分辨率加倍。此外,通过多对焦血管数据的融合结果验证了所提出的方法的有效性。我们的工作提供了可行的解决方案,用于实现大型,高分辨率光声学显微镜,用于进一步的数据分析,处理和应用。

As an important branch of photoacoustic microscopy, optical-resolution photoacoustic microscopy suffers from limited depth of field due to the strongly focused laser beam. In this work, a 3D information fusion algorithm based on 3D stationary wavelet transform and joint weighted evaluation optimization is proposed to fuse multi-focus photoacoustic data to achieve large-volumetric and high-resolution 3D imaging. First, a three-dimensional stationary wavelet transform was performed on the multi-focus data to obtain eight wavelet coefficients. Differential evolution algorithm based on joint weighted evaluation was then employed to optimize the block size of division for each wavelet coefficient. Corresponding sub-coefficients of multi-focus 3D data were fused with the proposed fusion rule utilizing standard deviation for focus detection. Finally, photoacoustic microscopy with large depth of field can be achieved by applying the inverse stationary wavelet transform on the 8 fused sub-coefficients. The fusion result of multi-focus vertically tilted fiber shows that the depth of field of optical-resolution photoacoustic microscopy is doubled without sacrificing lateral resolution via the proposed method. Furthermore, the effectiveness of the proposed method was verified through the fusion results of multi-focus vessel data. Our work provides a feasible solution for achieving large-volumetric, high-resolution photoacoustic microscopy for further data analysis, processing and applications.

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