Nonlinear super-resolution imaging in living zebrafish

被引:0
作者
Zhang, Chenshuang [1 ]
Qu, Junle [1 ]
机构
[1] Shenzhen Univ, Coll Phys & Optoelect Engn, Minist Educ & Guangdong Prov, Key Lab Optoelect Devices & Syst, Shenzhen 518060, Guangdong, Peoples R China
来源
MULTIPHOTON MICROSCOPY IN THE BIOMEDICAL SCIENCES XXIV | 2024年 / 12847卷
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Super-resolution; nonlinear imaging; adaptive optics; neurons; STRUCTURED ILLUMINATION MICROSCOPY; ADAPTIVE OPTICS; IMPROVES; RESOLUTION;
D O I
10.1117/12.3001303
中图分类号
TH742 [显微镜];
学科分类号
摘要
Optical microscopy has been indispensable for visualizing biological structure and function, while it remains a challenge since the limited diffraction resolution and restricted imaging depth. Nonlinear multifocal structured illumination microscopy (MSIM) provides resolution-doubled images and good penetration. Furthermore, adaptive optics (AO) is an effective method to recover spatial resolution and signal-to-noise ratio (SNR) in deep tissues and complex environments. Thus, we present a non-inertial scanning nonlinear MSIM system combined with AO to realize super-resolution imaging with aberration correction in vivo. Our strategy is designed to correct both laser and fluorescence paths simultaneously using a spatial light modulator and a deformable mirror respectively, providing better results than the individual path corrections. Furthermore, traditional approaches for MSIM image reconstruction at the expense of speed. Many raw images and iteration times are required for the reconstruction; besides, four steps in MSIM are separately accomplished in the reconstruction procedures of these methods. This is complicated and time-consuming, limiting extensive adoption of MSIM for practical use. To address the issues, a deep convolutional neural network to learn a direct mapping from raw MSIM images to super-resolution image, which takes advantage of the computational advances of deep learning to accelerate the reconstruction. The successful implementation of AO MSIM and fast MSIM reconstruction have allowed for the dynamic morphological characteristics of zebrafish motoneurons in vivo.
引用
收藏
页数:4
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