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通过瞳孔分割的自适应光学在生物组织中的高分辨率成像。

Adaptive optics via pupil segmentation for high-resolution imaging in biological tissues.

机构信息

Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia, USA.

出版信息

Nat Methods. 2010 Feb;7(2):141-7. doi: 10.1038/nmeth.1411. Epub 2009 Dec 27.

Abstract

Biological specimens are rife with optical inhomogeneities that seriously degrade imaging performance under all but the most ideal conditions. Measuring and then correcting for these inhomogeneities is the province of adaptive optics. Here we introduce an approach to adaptive optics in microscopy wherein the rear pupil of an objective lens is segmented into subregions, and light is directed individually to each subregion to measure, by image shift, the deflection faced by each group of rays as they emerge from the objective and travel through the specimen toward the focus. Applying our method to two-photon microscopy, we could recover near-diffraction-limited performance from a variety of biological and nonbiological samples exhibiting aberrations large or small and smoothly varying or abruptly changing. In particular, results from fixed mouse cortical slices illustrate our ability to improve signal and resolution to depths of 400 microm.

摘要

生物样本中存在着严重降低成像性能的光学非均质性,除非在最理想的条件下,否则这种情况会一直存在。测量并纠正这些非均质性是自适应光学的领域。在这里,我们介绍了一种在显微镜中的自适应光学方法,其中物镜的后孔径被分成子区域,然后将光单独引导到每个子区域,通过图像移位来测量每组光线从物镜出射并穿过样本到达焦点时所面临的偏折。将我们的方法应用于双光子显微镜,我们可以从各种表现出大或小、平滑变化或突然变化的像差的生物和非生物样本中恢复接近衍射极限的性能。特别是,来自固定的小鼠皮层切片的结果说明了我们能够将信号和分辨率提高到 400 微米的深度。

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