INSERM UMR901 INMED, Institut de Neurobiologie de la Méditerranée, Aix-Marseille Université, 13273 Marseille, France.
Aix-Marseille Université, CNRS, Centrale Marseille, Institut Fresnel UMR 7249, 13013 Marseille, France.
Sci Rep. 2017 Feb 21;7:42924. doi: 10.1038/srep42924.
Adaptive optics is a promising technique for the improvement of microscopy in tissues. A large palette of indirect and direct wavefront sensing methods has been proposed for in vivo imaging in experimental animal models. Application of most of these methods to complex samples suffers from either intrinsic and/or practical difficulties. Here we show a theoretically optimized wavefront correction method for inhomogeneously labeled biological samples. We demonstrate its performance at a depth of 200 μm in brain tissue within a sparsely labeled region such as the pyramidal cell layer of the hippocampus, with cells expressing GCamP6. This method is designed to be sample-independent thanks to an automatic axial locking on objects of interest through the use of an image-based metric that we designed. Using this method, we show an increase of in vivo imaging quality in the hippocampus.
自适应光学是一种有前途的技术,可以改善组织中的显微镜成像。已经提出了大量的间接和直接波前传感方法,用于实验动物模型中的活体成像。这些方法中的大多数在应用于复杂样本时都存在内在的和/或实际的困难。在这里,我们展示了一种针对不均匀标记生物样本的理论优化波前校正方法。我们在脑组织内的稀疏标记区域(如海马体的锥体细胞层)中展示了该方法在深度为 200μm 时的性能,其中有表达 GCamP6 的细胞。由于使用我们设计的基于图像的度量标准自动锁定感兴趣的目标,该方法具有样本独立性。使用这种方法,我们在海马体中展示了体内成像质量的提高。