FLOPA

FLOPA - FLIM Open, Process, and Analyze

A python based tool for Fluorescence Lifetime Imaging Microscopy (FLIM) data opening, processing and analysis. Designed as a modular widget for the napari multi-dimensional image viewer. Planned as napari plugin.

FLOPA tool is made to handle the TTTR files from various FLIM data acquisition settings, providing a clear interface for configuring reconstruction parameters and generating insightful data products like intensity/lifetime images, decay curves, and phasor plots.

1. PTU Reconstruction & Configuration	2. Pixel-based Phasor
3. Object-based Phasor	4. Decay Curve

---

Key Features

Currently implemented

• PTU file import
• header / metadata configuration option (lines, pixels, frames, sequences, accumulations)
• support for sequential and bidirectional scan (option to estimate and correct for bidirectional phase shift)
• preprocessing tools (binning, smoothing)
• intensity and mean arrival time image generation and export
• plotting TCSPC decay histograms
• phasor analysis (plot and export)
  • pixel-based phasor
  • object-based phasor (from label mask)

Planned functionalities

• batch processing widget
• multi-format data import (.sdt, and more)
• segmentation from phasor plot (interactive ROI selection)
• object-based TCSPC decay histograms
• decay fitting

---

Project Structure

The project is structured as a Python package, allowing its functions to be used in scripts and notebooks, with a top-level script for launching the napari GUI.

---

Installation and Usage

This project can be used in two ways: as a standalone napari application (recommended for interactive use) or as a Python library (for scripting and notebooks).

1. Installation

First, set up the project and install its dependencies.

• Prerequisites: Python 3.9+, Git
• Steps:
  1. Clone the repository:

     git clone https://your-repository-url/FLOPA.git
     cd FLOPA

  2. Create and activate a virtual environment:

     conda create --name flopa python=3.9
     conda activate flopa

  3. Install the package in editable mode: This installs all required dependencies from pyproject.toml and makes the flopa package importable.

     pip install -e .

2. Usage

Option A: Running the Napari Widget (interactive)

This is the primary method for interactive data exploration and analysis.

1. Make sure your virtual environment is activated.
2. Run the launch_napari.py script from the project's root directory:

   python launch_napari.py

This will launch a napari window with the full FLOPA widget docked and ready for you to load a file.

Option B: Using as a Python Library (for scripting and notebooks)

The core logic of FLOPA is accessible as a library, allowing you to build custom analysis workflows.

1. Make sure your virtual environment is activated.
2. Start a Python interpreter, an IPython session, or a Jupyter Notebook.
3. Import and use the functions directly.

• Navigate to the /notebooks directory to explore the example notebooks.