Membrane surface reconstruction at the nanometer scale is required for understanding mechanisms of subcellular shape change. This historically has been the domain of electron microscopy, but extraction of surfaces from specific labels is a difficult task in this imaging modality. Existing methods for extracting surfaces from fluorescence microscopy have poor resolution or require high-quality super-resolution data that are manually cleaned and curated. Here, we present NanoWrap, a new method for extracting surfaces from generalized single-molecule localization microscopy data. This makes it possible to study the shape of specifically labeled membranous structures inside cells. We validate NanoWrap using simulations and demonstrate its reconstruction capabilities on single-molecule localization microscopy data of the endoplasmic reticulum and mitochondria. NanoWrap is implemented in the open-source Python Microscopy Environment.
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