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Eigendecomposition-Based Clutter Filtering Technique for Optical Microangiography

机译:基于特征分解的光学微血管造影杂波滤波技术

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摘要

In this paper, we propose eigendecposition (ED)-based clutter filtering technique for 3-D optical imaging of blood flow. Due to its best mean-square approximation of the clutter, eigenregression filters can theoretically provide maximum clutter suppression. Compared to the existing clutter rejection techniques in the literature used for optical imaging of blood flow, ED-based clutter filtering is less sensitive to tissue motion and can efficiently suppress the clutter while preserving the flow information. Therefore, it creates images with better contrast in the presence of bulk motion. The performance of the proposed ED-based technique is compared with that of phase-compensation method and static high-pass filtering. The quantitative and qualitative performances are compared with each other in phantom studies and in vivo imaging, respectively. Also, 3-D image of microvascular structures in mouse ear is presented, where the clutter has been suppressed with ED-based technique. This technique can be used in applications, where involuntary movements due to cardiac and respiratory cycles are inevitable (such as retinal imaging).
机译:在本文中,我们提出了基于特征分解(ED)的杂波滤波技术来进行血流的3-D光学成像。由于其杂波的最佳均方近似值,本征回归滤波器理论上可以提供最大的杂波抑制。与文献中用于血流光学成像的现有杂波抑制技术相比,基于ED的杂波滤波对组织运动的敏感性较低,可以在保留流量信息的同时有效地抑制杂波。因此,在整体运动的情况下,它可以创建具有更好对比度的图像。将所提出的基于ED的技术的性能与相位补偿方法和静态高通滤波的性能进行了比较。定量和定性性能分别在幻像研究和体内成像中进行比较。此外,还提供了小鼠耳中微血管结构的3D图像,其中已使用基于ED的技术抑制了混乱。此技术可用于无法避免由于心脏和呼吸循环而导致的不自主运动的应用(例如视网膜成像)。

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