Active image optimization for lattice light sheet microscopy in thick samples

被引:10
作者
Malivert, Maxime [1 ,2 ]
Harms, Fabrice [2 ]
Veilly, Cynthia [2 ]
Legrand, Jerome [2 ]
Li, Ziqiang [3 ]
Bayer, Emmanuelle [3 ]
Choquet, Daniel [1 ,4 ]
Ducros, Mathieu [1 ]
机构
[1] Univ Bordeaux, Bordeaux Imaging Ctr BIC, CNRS, INSERM,UAR 3420,US 4, F-33000 Bordeaux, France
[2] Imagine Opt, F-91400 Orsay, France
[3] Univ Bordeaux, Lab Membrane Biogenesis LBM, CNRS, UMR 5200, F-33140 Villenave Dornon, France
[4] Univ Bordeaux, Interdisciplinary Inst Neurosci IINS, CNRS, UMR 5297, F-33000 Bordeaux, France
基金
欧洲研究理事会; 欧盟地平线“2020”;
关键词
SPECIMEN-INDUCED ABERRATIONS; ADAPTIVE OPTICS;
D O I
10.1364/BOE.471757
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Lattice light-sheet microscopy (LLSM) is a very efficient technique for high resolution 3D imaging of dynamic phenomena in living biological samples. However, LLSM imaging remains limited in depth due to optical aberrations caused by sample-based refractive index mismatch. Here, we propose a simple and low-cost active image optimization (AIO) method to recover high resolution imaging inside thick biological samples. AIO is based on (1) a light-sheet autofocus step (AF) followed by (2) an adaptive optics image-based optimization. We determine the optimum AIO parameters to provide a fast, precise and robust aberration correction on biological samples. Finally, we demonstrate the performances of our approach on sub-micrometric structures in brain slices and plant roots.
引用
收藏
页码:6211 / 6228
页数:18
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