SL2PM#
A package for tracking particles, red blood cells (RBCs), and microvessel walls with super-localization from images recorded with two-photon microscopy (2PM).
To get started with SL2PM, explore tutorials for tracking quantum dots, red blood cells, and capillaries. For example, if you are interested in measuring diameter of a capillary, made visible with fluorescently-labeled plasma (e.g. with FITC-dextran), see Tracking a capillary demo.
All tracking algorithms require calibration of the microscope’s photomultiplier tubes (Calibrating photomultiplier tubes) and, for tracking capillaries, calibration of the microscope’s point-spread function (Calibrating point-spread function for microvessel tracking).
The data analysis in SL2PM is data-driven, i.e., you need to check if underlying assumptions of SL2PM analysis are satisfied in your data before you apply any function from SL2PM. This is why we suggest using SL2PM with Jupyter notebooks, where you can explore your data step-by-step (following our examples) and tailor SL2PM analysis to your data, if needed.
Contents:
Tracking a quantum dot
Tracking a red blood cell
Tracking a capillary
Calibrating photomultiplier tubes
Calibrating point-spread function for microvessel tracking
Calibrating point-spread function for microvessel tracking with the `ultimate fit`
Removing artefact from output of photomultiplier tubes