小柯机器人

近日，清华大学戴琼海等研究人员合作发现，虚拟扫描光场显微镜可用于强大的快照高分辨率体积成像。相关论文于2023年4月6日在线发表在《自然—方法学》杂志上。

研究人员表示，动物的高速三维（3D）眼内成像对于研究健康和疾病中的瞬时亚细胞相互作用和功能非常有用。光场显微镜（LFM）为低光毒性的快照三维成像提供了一个计算解决方案，但受限于低分辨率和由光学像差、运动和噪声引起的重建伪影。

研究人员提出了虚拟扫描LFM（VsLFM），一个基于物理学的深度学习框架，将LFM的分辨率提高到快照中的衍射极限。通过构建一个跨越不同物种的40GB高分辨率扫描LFM数据集，研究人员利用相位相关角度视图之间的物理先验来解决频率混叠问题。这使研究人员能够绕过硬件扫描和相关的运动伪影。研究人员展示了VsLFM实现对不同过程的超高速三维成像，如胚胎斑马鱼的心脏跳动、果蝇大脑的电压活动和小鼠肝脏的中性粒细胞迁移，速度高达500体积/秒。

附：英文原文

Title: Virtual-scanning light-field microscopy for robust snapshot high-resolution volumetric imaging

Author: Lu, Zhi, Liu, Yu, Jin, Manchang, Luo, Xin, Yue, Huanjing, Wang, Zian, Zuo, Siqing, Zeng, Yunmin, Fan, Jiaqi, Pang, Yanwei, Wu, Jiamin, Yang, Jingyu, Dai, Qionghai

Issue&Volume: 2023-04-06

Abstract: High-speed three-dimensional (3D) intravital imaging in animals is useful for studying transient subcellular interactions and functions in health and disease. Light-field microscopy (LFM) provides a computational solution for snapshot 3D imaging with low phototoxicity but is restricted by low resolution and reconstruction artifacts induced by optical aberrations, motion and noise. Here, we propose virtual-scanning LFM (VsLFM), a physics-based deep learning framework to increase the resolution of LFM up to the diffraction limit within a snapshot. By constructing a 40GB high-resolution scanning LFM dataset across different species, we exploit physical priors between phase-correlated angular views to address the frequency aliasing problem. This enables us to bypass hardware scanning and associated motion artifacts. Here, we show that VsLFM achieves ultrafast 3D imaging of diverse processes such as the beating heart in embryonic zebrafish, voltage activity in Drosophila brains and neutrophil migration in the mouse liver at up to 500 volumes per second.

DOI: 10.1038/s41592-023-01839-6

Source: https://www.nature.com/articles/s41592-023-01839-6

Nature Methods：《自然—方法学》，创刊于2004年。隶属于施普林格·自然出版集团，最新IF：47.99
官方网址：https://www.nature.com/nmeth/
投稿链接：https://mts-nmeth.nature.com/cgi-bin/main.plex