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arXiv · 2610.17615

Background2Background: a self-supervised background removal framework for high dimensional microscopy

Guangrui Ding·Haonan Lin·Rong Tang·Bethany Weinberg·Jianpeng Ao·Qing Xia·Guorong Hu·Dingcheng Sun·Jiaze Yin·Lei Tian·Ji-Xin Cheng
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Abstract

High-dimensional microscopy captures features across space, time, and spectrum, but complex backgrounds obscure signals. We present Background2Background (B2B), a self-supervised background removal framework leveraging the backgrounds larger correlation relative to the signal. Local pixel shuffling disrupts signal correlations while preserving background structure, transforming signals into effective noise for Noise2Noise-based background removal. Across fluorescence, stimulated Raman scattering and mid-infrared photothermal imaging, B2B achieves over 40-fold background suppression and reveals hidden signatures.

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Guangrui Ding, Haonan Lin, Rong Tang, Bethany Weinberg, Jianpeng Ao, Qing Xia, Guorong Hu, Dingcheng Sun, Jiaze Yin, Lei Tian, Ji-Xin Cheng. 2026-10-13. Background2Background: a self-supervised background removal framework for high dimensional microscopy. https://arxiv.org/abs/2610.17615

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