大体积光学分辨率光声显微镜的三维融合

Xiongjun Cao, Zhihui Li, Xianlin Song
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引用次数: 2

摘要

光声成像已逐渐发展成为一种新兴的重要成像技术。光分辨率光声显微镜作为光声成像的一个重要分支,结合了光学成像和声成像的优点,具有高分辨率、高对比度、高灵敏度等优点。然而,为了获得高分辨率,往往需要对激光束进行强聚焦,这将导致景深小,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。在这里,我们提出了大体积光学分辨率光声显微镜的三维融合。首先,利用虚拟光声显微成像平台获得两组不同焦点位置的虚拟脑血管三维光声数据;然后,基于多尺度权重梯度融合算法,对小鼠脑血管b扫描数据进行融合,并对融合后的三维数据进行最大投影约简。最后,对融合前后的图像进行比较。实验结果表明,该算法可以有效地获得大体积、高分辨率的光声图像。
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Three-dimensional fusion for large volumetric optical-resolution photoacoustic microscopy
Photoacoustic imaging has gradually developed into a new and important imaging technology. As an important branch of photoacoustic imaging, optical-resolution photoacoustic microscopy combines the advantages of optical imaging and acoustic imaging, it has the advantages of high resolution, high contrast, high sensitivity and so on. However, in order to obtain high resolution, it is often necessary to focus the laser beam strongly, which will lead to the small depth of field and the inability to obtain large-scale structural information. However, in clinical diagnosis, doctors hope to obtain large-scale, 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. Here, we proposed three-dimensional fusion for large volumetric optical-resolution photoacoustic microscopy. Firstly, two groups of virtual cerebral vascular 3D photoacoustic data obtained at different focal locations were obtained by using virtual photoacoustic microscopic imaging platform. Then, based on the multi-scale weight gradient fusion algorithm, the B-scan data of mouse cerebrovascular data were fused, and the maximum projection reduction was performed on the fused 3D data. Finally, the images before and after fusion were compared. Experimental results show that this algorithm can effectively obtain large volumetric and high-resolution photoacoustic images.
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