Second-level high-speed 3D isotropic imaging of whole mouse brain using deep-learning spinning-disk light-sheet microscopy

Abstract Axially-swept light-sheet microscopy (ASLM) has emerged as a distinguished tool for 3D imaging owing to its excellent spatial resolution. However, the acquisition time is significantly elongated due to the extra time consumed in axial scanning. Meanwhile, the spatial information provided in a single scan is fundamentally limited by the compromise between field-of-view and resolution. The overall inadequate optical throughput of current ASLM techniques impedes their widespread application in acquiring large samples. Here we demonstrate a spinning-disk-based ASLM (SDLM) approach that enables wide field-of-view (15 × confocal range of the gaussian beam), isotropic 3D imaging of large organisms at 100 Hz full camera frame rate. In addition to the new optical design, we combine a recurrent neural network image restoration model to further improve the resolution of raw images. We demonstrate seconds scale stitching-free 3D imaging of the entire mouse brain (~ 9*8*5 mm size) at isotropic single-cell resolution (1.5 µm voxel). With the high-quality data readily obtained by our approach, we also demonstrate the visualization of long projecting neurons and two genotypes of whole mouse brain cell profiling across the 3D space. Further transformation into in vivo research would broaden the application of SDLM.

Authors

Institutions

Publication Details

Journal
PhotoniX
Published
2025-10-15
DOI
https://doi.org/10.1186/s43074-025-00200-8
Citations
1
Primary Topic
Advanced Fluorescence Microscopy Techniques
Type
article
Field-Weighted Citation Impact
1.63

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Second-level high-speed 3D isotropic imaging of whole mouse brain using deep-learning spinning-disk light-sheet microscopy

Yuyi Wang, Fenghe Zhong, Chaoliang Ye, Zhaofei Wang et al.
1 citations
PhotoniX
Advanced Fluorescence Microscopy Techniques
1.63
article

Second-level high-speed 3D isotropic imaging of whole mouse brain using deep-learning spinning-disk light-sheet microscopy

Yuyi Wang, Fenghe Zhong, Chaoliang Ye, Zhaofei Wang, Jingtan Zhu, Dan Zhu, Peng Fei, Junyu Ping, Yuan Wang, Xingyu Chen, Fang Zhao, Man Jiang, Yuxuan Zhao
article en
1 citations

Abstract

Abstract Axially-swept light-sheet microscopy (ASLM) has emerged as a distinguished tool for 3D imaging owing to its excellent spatial resolution. However, the acquisition time is significantly elongated due to the extra time consumed in axial scanning. Meanwhile, the spatial information provided in a single scan is fundamentally limited by the compromise between field-of-view and resolution. The overall inadequate optical throughput of current ASLM techniques impedes their widespread application in acquiring large samples. Here we demonstrate a spinning-disk-based ASLM (SDLM) approach that enables wide field-of-view (15 × confocal range of the gaussian beam), isotropic 3D imaging of large organisms at 100 Hz full camera frame rate. In addition to the new optical design, we combine a recurrent neural network image restoration model to further improve the resolution of raw images. We demonstrate seconds scale stitching-free 3D imaging of the entire mouse brain (~ 9*8*5 mm size) at isotropic single-cell resolution (1.5 µm voxel). With the high-quality data readily obtained by our approach, we also demonstrate the visualization of long projecting neurons and two genotypes of whole mouse brain cell profiling across the 3D space. Further transformation into in vivo research would broaden the application of SDLM.

PhotoniXVol. 6(1)
Wuhan National Laboratory for Optoelectronics (CN), Huazhong University of Science and Technology (CN)
National Natural Science Foundation of China, China Postdoctoral Science Foundation, National Key Research and Development Program of China
Openalex Percentile: Top 12%
Advanced Fluorescence Microscopy Techniques
1.63
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.