A reader plugin for read iacs/ipac images and export .rtdc files.

    License PyPI Python Version tests codecov napari hub

    A plugin used a convolutional neural network (CNN) to distinguish single platelets, platelet clusters, and white blood cells and performed classical image analysis for each subpopulation individually. Based on the derived single-cell features for each population, a Random Forest (RF) model was trained and used to classify COVID-19 associated thrombosis and non-COVID-19 associated thrombosis.

    More information about IACS/iPAC.
    IACS: DOI: 10.1016/j.cell.2018.08.028
    iPAC: DOI: 10.7554/eLife.52938

    This napari plugin was generated with Cookiecutter using @napari's cookiecutter-napari-plugin template.


    You can install iacs_ipac_reader via pip:

    pip install iacs_ipac_reader

    To install latest development version :

    pip install git+https://github.com/zcqwh/iacs_ipac_reader.git


    The iacs-ipac-reader plugin mainly include 3 functional tabs:

    • iPAC
    • IACS
    • AID classif.

    iPAC image contour tracker

    Interface of iPAC contour tracker


    IACS image contour tracker

    Interface of IACS contour tracker


    AID classif.

    Interface of AID classif.



    Contributions are very welcome. Tests can be run with tox, please ensure the coverage at least stays the same before you submit a pull request.


    Distributed under the terms of the BSD-3 license, "iacs_ipac_reader" is free and open source software


    If you encounter any problems, please file an issue along with a detailed description.


    • 0.0.13

    Release date:

    • 12 April 2022

    First released:

    • 21 January 2022


    • BSD-3-Clause

    Supported data:

    • Information not submitted

    GitHub activity:

    • Stars: 0
    • Forks: 0
    • Issues + PRs: 0

    Python versions supported:

    Operating system:


    • h5py (>=3.5.0)
    • napari (>=0.4.12)
    • napari-plugin-engine (>=0.2.0)
    • numpy (>=1.21.4)
    • opencv-contrib-python-headless (>=
    • openpyxl (>=3.0.9)
    • sklearn (>=0.0)
    • PyQt5 (==5.12.3)
    • pandas (>=1.4.0)

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