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Identification, Restoration in 3-D Fluorescence Microscopy

机译:在3-D荧光显微镜中的鉴定,修复

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摘要

3-D optical fluorescent microscopy becomes now an efficient tool for volumic investigation of living biological samples. The 3-D data can be acquired by Optical Sectioning Microscopy which is performed by axial stepping of the object versus the objective. For any instrument, each recorded image can be described by a convolution equation between the original object and the Point Spread Function (PSF) of the acquisition system. To assess performance and ensure the data reproducibility, as for any 3-D quantitative analysis, the system indentification is mandatory. The PSF explains the properties of the image acquisition system; it can be computed or acquired experimentally. Statistical tools and Zernike moments are shown appropriate and complementary to describe a 3-D system PSF and to quantify the variation of the PSF as function of the optical parameters. Some critical experimental parameters can be identified with these tools. This is helpful for biologist to define an acquisition protocol optimizing the use of the system. Reduction of out-of-focus light is the task of 3-D microscopy; it is carried out computationally by deconvolution process. Pre-filtering the images improves the stability of deconvolution results, now less dependent on the regularization parameter; this helps the biologists to use restoration process.
机译:3-D光学荧光显微镜现已成为对活生物样品进行大量研究的有效工具。可以通过光学切片显微镜获取3D数据,该方法是通过物体相对于物镜的轴向步进来执行的。对于任何仪器,每个记录的图像都可以通过原始对象与采集系统的点扩展函数(PSF)之间的卷积方程来描述。为了评估性能并确保数据可重复性,对于任何3-D定量分析,系统标识都是强制性的。 PSF解释了图像采集系统的属性;可以通过实验来计算或获取。统计工具和Zernike矩被显示为适当和互补的,以描述3-D系统PSF并量化PSF随光学参数变化的变化。可以使用这些工具识别一些关键的实验参数。这对于生物学家定义优化系统使用的采集协议很有帮助。减少散焦光是3-D显微镜的任务;它通过反卷积过程进行计算。对图像进行预滤波可提高解卷积结果的稳定性,现在对正则化参数的依赖性降低了;这有助于生物学家使用修复过程。

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