Abstract
We present a deep learning-based methodology to enable simultaneous spectral and lifetime unmixing for quantitative multiplexed imaging. We demonstrate the approach’s performance both in silico (tri/quadri-specie retrieval) and experimentally (in vitro and in vivo).
© 2020 The Author(s)
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