@article {70383,
	title = {Mico <i>S</I> plit: semantic unmixing of fluorescent microscopy data},
	journal = {Nat Methods},
	year = {2026},
	month = {2026 May 05},
	abstract = {<p>Fluorescence microscopy is constrained by optical limits, fluorophore chemistry and finite photon budgets, imposing trade-offs between imaging speed, resolution and phototoxicity. Here we introduce MicroSplit, a deep learning-based computational multiplexing method that enables multiple cellular structures to be imaged simultaneously in a single fluorescent channel and then computationally unmixed. We show that\&nbsp;MicroSplit separates up to four superimposed noisy structures into distinct, denoised image channels, enabling faster and more photon-efficient imaging. Built on Variational Splitting Encoder-Decoder networks,\&nbsp; MicroSplit\&nbsp;models a posterior distribution over solutions, allowing uncertainty-aware predictions and the estimation of spatially resolved prediction errors from posterior variability. We demonstrate robust performance across diverse datasets, noise levels and imaging conditions, and show that\&nbsp; MicroSplit\&nbsp;improves downstream analysis while reducing photon exposure. All methods, data and trained models are released as open resources, enabling immediate adoption of computational multiplexing in biological imaging.</p>
},
	issn = {1548-7105},
	doi = {10.1038/s41592-026-03082-1},
	url = {https://doi.org/10.1038/s41592-026-03082-1},
	author = {Ashesh, Ashesh and Carrara, Federico and Zubarev, Igor and Galinova, Vera and Croft, Melisande and Pezzotti, Melissa and Gong, Daozheng and Casagrande, Francesca and Colombo, Elisa and Giussani, Stefania and Restelli, Elena and Cammarota, Eugenia and Battagliotti, Juan Manuel and Klena, Nikolai and Di Sante, Moises and Adhikari, Raghabendra and Feliciano, Daniel and Pigino, Gaia and Taverna, Elena and Harschnitz, Oliver and Maghelli, Nicola and Scherer, Norbert and Dalle Nogare, Damian Edward and Deschamps, Joran and Pasqualini, Francesco and Jug, Florian}
}
