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Wrinkle Image Registration for Serial Microscopy Sections

机译:连续显微镜切片的皱纹图像配准

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3D Reconstruction from the microscopy images of serial sections plays an important role in analysis structure of biological specimens, such as neuronal circuits in brain tissue. During specimen sectioning and collecting, it is very hard to prevent wrinkle from these sections, which introduce distortion when imaging in electron microscopy and cause failure of structure reconstruction. In this paper, we propose a pipeline for registration of serial sections with wrinkle. First, Scale Invariant Feature Transform (SIFT) is used to detect corresponding landmarks across adjacent sections. Second, wrinkle areas are labeled manually in microscopy images, which is easy to distinguish by eye. Finally, a modified Moving-Least-Square deformation algorithm is applied to register adjacent sections with wrinkle. The algorithm reflects the discontinuity around wrinkle areas while keeps the smoothness in other regions. Experimental results demonstrate the effectiveness of our method.
机译:连续切片显微镜图像的3D重建在生物标本(例如脑组织中的神经元回路)的分析结构中起着重要作用。在标本切片和收集过程中,很难防止这些切片出现褶皱,皱纹会在电子显微镜成像时引入变形并导致结构重建失败。在本文中,我们提出了用于皱纹系列切片的配准的管道。首先,尺度不变特征变换(SIFT)用于检测相邻断面的相应界标。其次,在显微镜图像中手动标记皱纹区域,这很容易用肉眼区分。最后,采用改进的移动最小二乘变形算法来记录相邻区域的褶皱。该算法反映了皱纹区域周围的不连续性,同时保持了其他区域的平滑度。实验结果证明了该方法的有效性。

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