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Development of a method for the measurement of primary cilia length in 3D

机译:开发用于在3D模式下测量初级纤毛长度的方法

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Background Primary cilia length is an important measure of cell and tissue function. While accurate length measurements can be calculated from cells in 2D culture, measurements in tissue or 3D culture are inherently difficult due to optical distortions. This study uses a novel combination of image processing techniques to rectify optical distortions and accurately measure cilia length from 3D images. Methods Point spread functions and experimental resolutions were calculated from subresolution microspheres embedded in 3D agarose gels for both wide-field fluorescence and confocal laser scanning microscopes. The degree of axial smearing and spherical aberration was calculated from xy:xz diameter ratios of 3D image data sets of 4 μm microspheres that had undergone deconvolution and/or Gaussian blurring. Custom-made 18 and 50 μm fluorescent microfibers were also used as calibration objects to test the suitability of processed image sets for 3D skeletonization. Microfiber length in 2D was first measured to establish an original population mean. Fibers were then embedded in 3D agarose gels to act as ciliary models. 3D image sets of microfibers underwent deconvolution and Gaussian blurring. Length measurements within 1 standard deviation of the original 2D population mean were deemed accurate. Finally, the combined method of deconvolution, Gaussian blurring and skeletonization was compared to previously published methods using images of immunofluorescently labeled renal and chondrocyte primary cilia. Results Deconvolution significantly improved contrast and resolution but did not restore the xy:xz diameter ratio (0.80). Only the additional step of Gaussian blurring equalized xy and xz resolutions and yielded a diameter ratio of 1.02. Following image processing, skeletonization successfully estimated microfiber boundaries and allowed reliable and repeatable measurement of fiber lengths in 3D. We also found that the previously published method of calculating length from 2D maximum projection images significantly underestimated ciliary length. Conclusions This study used commercial and public domain image processing software to rectify a long-standing problem of 3D microscopy. We have shown that a combination of deconvolution and Gaussian blurring rectifies optical distortions inherent in 3D images and allows accurate skeletonization and length measurement of microfibers and primary cilia that are bent or curved in 3D space.
机译:背景初级纤毛长度是细胞和组织功能的重要指标。尽管可以从2D培养中的细胞计算出精确的长度测量值,但由于光学畸变,组织或3D培养中的测量固有地困难。这项研究使用图像处理技术的新颖组合来纠正光学畸变并从3D图像准确测量纤毛长度。方法从嵌入在3D琼脂糖凝胶中的亚分辨率微球体(用于宽视场荧光显微镜和共聚焦激光扫描显微镜)计算点扩散函数和实验分辨率。根据经过解卷积和/或高斯模糊的4μm微球的3D图像数据集的xy:xz直径比,计算轴向拖尾和球面像差的程度。定制的18和50μm荧光微纤维也被用作校准对象,以测试处理后的图像集是否适合3D骨架化。首先测量2D中的超细纤维长度,以建立原始总体平均值。然后将纤维嵌入3D琼脂糖凝胶中,作为纤毛模型。微纤维的3D图像集进行了反卷积和高斯模糊处理。在原始2D总体平均值的1个标准偏差内的长度测量被认为是准确的。最后,将反卷积,高斯模糊和骨架化的组合方法与先前发表的使用免疫荧光标记的肾脏和软骨细胞原发纤毛的图像进行比较。结果解卷积显着改善了对比度和分辨率,但未恢复xy:xz直径比(0.80)。只有高斯模糊的附加步骤才能使xy和xz分辨率相等,并且直径比为1.02。经过图像处理后,骨架化成功地估计了超细纤维的边界,并允许对3D纤维长度进行可靠且可重复的测量。我们还发现,以前发布的从2D最大投影图像计算长度的方法明显低估了睫毛长度。结论这项研究使用了商业和公共领域的图像处理软件来纠正长期存在的3D显微镜问题。我们已经证明,反卷积和高斯模糊的组合可以纠正3D图像固有的光学畸变,并可以对在3D空间中弯曲或弯曲的微纤维和初级纤毛进行精确的骨架化和长度测量。

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