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Unsupervised deep learning enables blur-free resolution enhancement in two-photon microscopy
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DOI：10.1016/j.crmeth.2026.101476.png)
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Abstract
En 中文
• TENET is an unsupervised framework for deblurring, super-resolution, and segmentation • It can be trained without paired ground-truth images via a physics-informed module • TENET achieves high fidelity and segmentation accuracy compared to previous methods • It reveals dynamic microglia-tumor interactions inaccessible to standard pipelines
Keywords:
multiphoton excitation microscopy, unsupervised machine learning, autoencoder, microglia
CP: imaging
CP: systems biology
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