3D information fusion of optical-resolution photoacoustic microscopy for extended depth of field using pyramid transform

Xiongjun Cao, Zhihui Li, Xianlin Song
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Abstract

In recent years, more and more organizations and teams in the world are engaged in photoacoustic imaging research. Photoacoustic imaging is in a state of vigorous development. As an important branch of photoacoustic microscopy, optical resolution photoacoustic microscopy combines the advantages of optical imaging and acoustic imaging, which has the advantages of high resolution, high contrast, high sensitivity and non-invasiveness. However, in order to obtain high resolution, it is often necessary to focus the laser beam, which will lead to small imaging depth of field and unable to obtain large-scale structural information. However, in clinical diagnosis, doctors want to obtain large-scale and high-resolution structural and functional information as much as possible, so it is of great significance to solve the problem of small depth of field in photoacoustic microscopy. In order to expand the depth of field of photoacoustic microscopy imaging, this paper proposes a three-dimensional information fusion algorithm for photoacoustic microscopy imaging. Firstly, we obtain two sets of vascular data (except the focus position) by virtual photoacoustic microscopy. Then we take out the B scan data of two sets of three-dimensional data sets in turn, and use the fusion algorithm based on pyramid transform to fuse them. Finally, the maximum projection is used to restore the original data and the fused data. We compare the maximum projection before and after fusion. The experimental results show that the algorithm realizes the extension of the depth of field, and the fused data successfully displays more abundant vascular information in an image, and maintains the advantages of high contrast and high resolution of photoacoustic microscopy imaging.
基于金字塔变换的扩展景深光学分辨率光声显微镜三维信息融合
近年来,国际上从事光声成像研究的机构和团队越来越多。光声成像正处于蓬勃发展的状态。光学分辨率光声显微镜作为光声显微镜的一个重要分支,结合了光学成像和声成像的优点,具有高分辨率、高对比度、高灵敏度和无创性等优点。然而,为了获得高分辨率,往往需要对激光束进行聚焦,这将导致成像景深小,无法获得大尺度的结构信息。但在临床诊断中,医生希望尽可能获得大尺度、高分辨率的结构和功能信息,因此解决光声显微镜的小景深问题具有重要意义。为了扩大光声显微镜成像的景深,提出了一种用于光声显微镜成像的三维信息融合算法。首先,我们利用虚拟光声显微镜获得了两组血管数据(焦点位置除外)。然后,我们依次取出两组三维数据集的B扫描数据,使用基于金字塔变换的融合算法进行融合。最后利用最大投影法恢复原始数据和融合后的数据。我们比较了融合前后的最大投影。实验结果表明,该算法实现了景深的扩展,融合后的数据成功地在图像中显示了更丰富的血管信息,保持了光声显微镜成像的高对比度和高分辨率的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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