北京大学Xi Peng课题组取得一项新突破。他们的最新研究揭示了暗基光学切片有助于荧光显微镜去除背景。2025年5月12日出版的《自然—方法学》杂志发表了这项成果。

课题组研究人员介绍暗分割，灵感来自自然图像去雾去除背景，利用暗通道先验和双频分离，以提供单帧光学分割的方法。与去噪或反卷积不同，Dark切片专门针对并去除焦外背景，稳定地将信背景比提高近10 dB，将图像的结构相似性指数提高约10倍。暗切片采用宽视场、共聚焦、二/三维结构照明和高保真重建的单/双光子显微镜进行验证。

小组进一步证明了其在深层组织中提高分割准确性的潜力，从而更好地识别无母细胞脑中的神经元，并准确评估前列腺病变或无母细胞脑切片中的细胞核。暗切片与许多其他显微镜模式兼容，包括光片和光场显微镜，以及处理算法，包括反卷积和超分辨率光学波动成像。

据介绍，在荧光显微镜中，一个持续的挑战是分散焦点的背景，它模糊了细胞的细节并引入了伪影。

附：英文原文

Title: Dark-based optical sectioning assists background removal in fluorescence microscopy

Author: Cao, Ruijie, Li, Yaning, Zhou, Yao, Li, Meiqi, Lin, Fangrui, Wang, Wenyi, Zhang, Guoxun, Wang, Gang, Jin, Boya, Ren, Wei, Sun, Yu, Zhao, Zhifeng, Zhang, Wei, Sun, Jing, Hou, Yiwei, Xu, Xinzhu, Hu, Jiakui, Shi, Wei, Fu, Shuang, Liang, Qianxi, Lu, Yanye, Li, Changhui, Zhao, Yuxuan, Li, Yiming, Kuang, Dong, Wu, Jiamin, Fei, Peng, Qu, Junle, Xi, Peng

Issue&Volume: 2025-05-12

Abstract: In fluorescence microscopy, a persistent challenge is the defocused background that obscures cellular details and introduces artifacts. Here, we introduce Dark sectioning, a method inspired by natural image dehazing for removing backgrounds that leverages dark channel prior and dual frequency separation to provide single-frame optical sectioning. Unlike denoising or deconvolution, Dark sectioning specifically targets and removes out-of-focus backgrounds, stably improving the signal-to-background ratio by nearly 10 dB and structural similarity index measure of images by approximately tenfold. Dark sectioning was validated using wide-field, confocal, two/three-dimensional structured illumination and one/two-photon microscopy with high-fidelity reconstruction. We further demonstrate its potential to improve the segmentation accuracy in deep tissues, resulting in better recognition of neurons in the mouse brain and accurate assessment of nuclei in prostate lesions or mouse brain sections. Dark sectioning is compatible with many other microscopy modalities, including light-sheet and light-field microscopy, as well as processing algorithms, including deconvolution and super-resolution optical fluctuation imaging.

DOI: 10.1038/s41592-025-02667-6

Source: https://www.nature.com/articles/s41592-025-02667-6