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Guide star based deconvolution for imaging behind turbid media
Journal of the European Optical Society-Rapid Publications ( IF 1.5 ) Pub Date : 2018-10-03 , DOI: 10.1186/s41476-018-0089-5
Jale Schneider , Christof M Aegerter

If structures of interest are hidden beneath turbid layers such as biological tissues, imaging becomes challenging, even impossible. However, if the point spread function of the system is known from the presence of a guide star, application of common deconvolution algorithms can be a convenient approach to reconstruct even heavily scrambled images. In this work, we present the severity of scattering and the capability of deconvolution techniques in optical settings realistically mimicking biological applications. We determine the point spread function (PSF) of the optical path using a single fluorescent bead hidden behind a scattering layer. Once the PSF is obtained, a scene containing several beads is brought to the exact the same position behind the scattering layer. The scrambled image of the scene is then deconvoluted with the PSF. Plastic films and thin slices of chicken tissues are used as scattering layers. Despite the low signal provided by small fluorescent particles and their short distance of a few millimeters to the turbid media, the reconstructed images reproduced the original scenes successfully. The spatial variance of the PSF caused by the inhomogeneous scattering layer mainly limited the size of the reconstructed area. Our method overcomes the negative effects of scattering on the detection side of an imaging system. However, it can be combined with wavefront shaping methods optimizing the illumination path as well leading to even further increase of signal to noise ratio and image quality. The required guide star can be brought inside the biological sample to a desired position using optical fibers as a light guide or using capillaries filled with bright fluorescent molecules.

中文翻译:

基于导星的反卷积,用于在浑浊的介质后面成像

如果感兴趣的结构隐藏在诸如生物组织之类的混浊层之下,则​​成像变得具有挑战性,甚至是不可能的。但是,如果从引导星的存在中知道系统的点扩展函数,则常见的反卷积算法的应用可能是一种方便的方法,甚至可以重建严重加扰的图像。在这项工作中,我们提出了散射的严重程度以及在实际模仿生物学应用的光学环境中的解卷积技术的能力。我们使用隐藏在散射层后面的单个荧光珠来确定光路的点扩散函数(PSF)。一旦获得PSF,就将一个包含几个小珠的场景带到散射层后面的确切相同位置。然后用PSF对场景的加密图像进行反卷积。塑料薄膜和鸡组织薄片用作散射层。尽管小的荧光颗粒提供的信号很弱,并且它们与混浊的介质之间只有几毫米的短距离,但是重建的图像仍成功地再现了原始场景。由不均匀散射层引起的PSF的空间变化主要限制了重建区域的大小。我们的方法克服了散射对成像系统检测侧的负面影响。但是,它可以与优化照明路径的波前整形方法结合使用,从而进一步提高信噪比和图像质量。
更新日期:2018-10-03
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