Phasor Identifier: A Cloud-based Analysis of Phasor-FLIM Data on Python Notebooks

Abstract This study aims at creating an accessible notebook tool for the versatile analysis of phasor Fluorescence Lifetime Imaging Microscopy (FLIM) data collected from various samples (e.g. cuvette, cells, tissues) and in various input file formats. The presented strategy facilitates morphological segmentations and diverse mask imports. Results derived from three compelling case studies involving cellular metabolism, nanoscale drug encapsulation (doxorubicin), and the impact of pH and metabolic cleavage on small fluorescent drugs (irinotecan), showcase extensive analysis capabilities. The notebook-centered approach accelerates phasor-FLIM data analysis via external servers, supporting multi-scale research and avoiding the need for GPUs, RAM, and disk space.