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Since October 1, 2024, this version is no longer actively maintained and will not be updated. New plugins and plugin updates will continue to be listed.

T-MIDAS

napari-tmidas

Tissue Microscopy Image Data Analysis Suite

Workflow step:
Image annotation
Image segmentation

License BSD-3 PyPI Python Version tests napari hub

The Tissue Microscopy Image Data Analysis Suite (short: T-MIDAS), is a collection of pipelines for batch image preprocessing, segmentation, regions-of-interest (ROI) analysis and other useful features. This is a work in progress (WIP) and an evolutionary step away from the terminal / command-line version of T-MIDAS.

Installation

First install Napari in a virtual environment following the latest Napari installation instructions.

After you have activated the environment, you can install napari-tmidas via pip:

pip install napari-tmidas

To install the latest development version:

pip install git+https://github.com/macromeer/napari-tmidas.git

Usage

File inspector

  1. You can find the installed plugin here:

image

  1. After opening the plugin, select the folder with the images to be processed (currently supports TIF, later also ZARR). You can also filter for filename suffix.

image

  1. As a result, a table appears with the found images.

image

  1. Next, select a processing function, set parameters if applicable and start batch processing.

image

  1. You can click on the images to show them in the viewer. For example first click on one of the Original Files, and then the corresponding Processed File to see an overlay.

image

Whenever you click on an Original File or Processed File in the table, it will replace the one that is currently shown in the viewer. So naturally, you'd first select the original image, and then the processed image to correctly overlay the image pair that you want to inspect.

Label inspector

If you have already segmented a folder full of images and now you want to maybe inspect and edit each label image, you can use the Label inspector, which automatically saves your changes to the existing label image once you click the Save and Continue button.

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Contributing

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.

License

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

Issues

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


This napari plugin was generated with copier using the napari-plugin-template.

Version:

  • 0.1.2

Last updated:

  • 10 March 2025

First released:

  • 05 March 2025

License:

Supported data:

  • Information not submitted

Open extension:

Save extension:

Save layers:

GitHub activity:

  • Stars: 3
  • Forks: 0
  • Issues + PRs: 0

Python versions supported:

Operating system:

Requirements:

  • numpy
  • magicgui
  • qtpy
  • scikit-image
  • pyqt5