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NATURE METHODS · 2025 · IF 32.1

Dark-based optical sectioning assists background removal in fluorescence microscopy

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

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.

CAS / MDL: 17372-87-1
研究领域: 显微镜技术 · 生物成像 · 计算成像 · 细胞生物学 · 神经科学 · 生物医学工程
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