论文标题
三维偏振光成像中噪声和伪影去除的独立组件分析
Independent Component Analysis for noise and artifact removal in Three-dimensional Polarized Light Imaging
论文作者
论文摘要
近年来，独立组件分析（ICA）已成功应用于从中尺度上的三维偏振光成像（3D-PLI）获得的图像中删除噪声和伪影（即64 $μ$ m）。在这里，我们为灰质区域提出了一个自动降解程序，该程序允许通过合理的计算工作将ICA应用于显微镜图像。除了对灰质区域的自动分割外，我们还将denoisising程序应用于大鼠和一个猴子脑部部分的几个3D-PLI图像。
In recent years, Independent Component Analysis (ICA) has successfully been applied to remove noise and artifacts in images obtained from Three-dimensional Polarized Light Imaging (3D-PLI) at the mesoscale (i.e., 64 $μ$m). Here, we present an automatic denoising procedure for gray matter regions that allows to apply the ICA also to microscopic images, with reasonable computational effort. Apart from an automatic segmentation of gray matter regions, we applied the denoising procedure to several 3D-PLI images from a rat and a vervet monkey brain section.
