清华大学Qionghai Dai，Li Yu和Jiamin Wu共同合作，近期取得重要工作进展。他们研究开发了自监督图像增强显微技术，能够通过该技术进行生物友好型长期亚细胞动态记录。相关研究成果2023年11月13日在线发表于《自然—方法学》杂志上。

据介绍，荧光显微镜已成为揭示细胞和细胞器动态调控的不可或缺的工具。然而，当平衡高帧率、长期记录和低光毒性的共同需求时，随机噪声固有地限制了光学询问质量，并加剧了观测保真度。

研究人员提出了DeepSeMi，一种基于自监督学习的去噪框架，能够在各种条件下将信噪比提高12 dB以上。通过引入新设计的偏心盲点卷积滤波器，DeepSeMi在不损失时空分辨率的情况下有效地对图像进行去噪。DeepSeMi与共聚焦显微镜相结合，可以在数万帧内以高帧率记录四种颜色的细胞器相互作用，在半天内监测迁移体和收缩体，并在数千帧内对超光毒性敏感的盘状骨细胞成像。

总之，通过对各种样品和仪器的全面验证，研究人员证明，DeepSeMi是一种多功能、生物相容的工具，可以突破散粒噪声限制。

附：英文原文

Title: Bio-friendly long-term subcellular dynamic recording by self-supervised image enhancement microscopy

Author: Zhang, Guoxun, Li, Xiaopeng, Zhang, Yuanlong, Han, Xiaofei, Li, Xinyang, Yu, Jinqiang, Liu, Boqi, Wu, Jiamin, Yu, Li, Dai, Qionghai

Issue&Volume: 2023-11-13

Abstract: Fluorescence microscopy has become an indispensable tool for revealing the dynamic regulation of cells and organelles. However, stochastic noise inherently restricts optical interrogation quality and exacerbates observation fidelity when balancing the joint demands of high frame rate, long-term recording and low phototoxicity. Here we propose DeepSeMi, a self-supervised-learning-based denoising framework capable of increasing signal-to-noise ratio by over 12dB across various conditions. With the introduction of newly designed eccentric blind-spot convolution filters, DeepSeMi effectively denoises images with no loss of spatiotemporal resolution. In combination with confocal microscopy, DeepSeMi allows for recording organelle interactions in four colors at high frame rates across tens of thousands of frames, monitoring migrasomes and retractosomes over a half day, and imaging ultra-phototoxicity-sensitive Dictyostelium cells over thousands of frames. Through comprehensive validations across various samples and instruments, we prove DeepSeMi to be a versatile and biocompatible tool for breaking the shot-noise limit.

DOI: 10.1038/s41592-023-02058-9

Source: https://www.nature.com/articles/s41592-023-02058-9