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Ultra-multiplexed fluorescence imaging has revolutionized our understanding of biological systems, enabling the simultaneous visualization and quantification of multiple targets within biological specimens. A recent breakthrough in this field is PICASSO, a mutual-information-based technique capable of demixing up to 15 fluorophores without their spectra, thereby significantly simplifying the application of ultra-multiplexed fluorescence imaging. However, this study has identified a limitation of mutual information (MI)-based techniques. They do not differentiate between spatial colocalization and spectral mixing. Consequently, MI-based demixing may incorrectly interpret spatially co-localized targets as non-colocalized, leading to overcorrection.
Pubmed ID: 38175779
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Multi paradigm numerical computing environment and fourth generation programming language developed by MathWorks. Allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, Java, Fortran and Python. Used to explore and visualize ideas and collaborate across disciplines including signal and image processing, communications, control systems, and computational finance.
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