Platelet Tracking and Thrombi Analysis Tool

This Python tool provides a pipeline for analyzing microscopy videos of blood flow, enabling the tracking of individual platelets and the quantification of thrombi formation and platelet accumulation over time.

Features

• Automated Analysis: Processes .tif image stacks (microscopy videos) to extract key information about platelet movement, thrombi formation, and platelet accumulation.
• Platelet Tracking: dentifies and tracks individual platelets across video frames.
• Thrombi and Platelet Accumulation Characterization: Quantifies thrombi formation and platelet accumulation by calculating the area and count of both thrombi and individual platelets in each frame.
• Data Output: Generates CSV files containing thrombi data, platelet data, and tracked platelet information for further analysis.
• Optional Visualization: Enables interactive visualization of the original video, labeled platelets, and tracked platelet paths using Napari.

Installation

1. Clone the repository:

   git clone https://gitlab.com/lerakaneva/tracking_tool.git
   cd tracking_tool
   
   

2. Install dependencies:

   pip install -r requirements.txt

Usage

To process and analyze .tif mask files in a directory, run:

python tracking.py /path/to/tif/files --visualize

• Replace /path/to/tif/files with the directory containing your .tif files.

Dependencies

• numpy
• pandas
• scikit-image
• tifffile
• trackpy
• napari

All dependencies are specified in requirements.txt.

Output

The tool will process each .tif file in the specified directory and create corresponding output files organized into subdirectories within the same directory. For a video file named example_video.tif, the following outputs will be generated:

- Thrombi Data: (saved in the ThrombiAreas and ThrombiNumbers subdirectories, respectively)

- `example_video_thrombi_areas.csv`: Contains the percentage of area covered by thrombi in each frame of the video.
- `example_video_thrombi_number.csv`: Contains the number of thrombi detected in each frame of the video.

- Platelet Data: (saved in the PlateletAreas and PlateletNumbers subdirectories, respectively)

- `example_video_platelet_areas.csv`: Contains the area covered by platelets in each frame.
- `example_video_platelet_number.csv`: Contains the number of platelets detected in each frame.

- Tracked Platelet Data: (saved in the Tracked CSV subdirectory)

- `example_video_tracked.csv`: Contains the tracked positions of individual platelets over time.  The file has the following columns:
    - `x`: x-coordinate of the platelet in the image.
    - `y`: y-coordinate of the platelet in the image.
    - `frame_y`: Frame number (time point) of the measurement.
    - `track_id`: Unique identifier for each tracked platelet.

- Napari Visualization (if --visualize is used):

- A multi-page TIFF file named `example_video.tif` containing the original video, labeled platelets, and tracked platelet paths, viewable in Napari. This file will be saved in a subdirectory named `Napari`.