Skip to main content

No project description provided

Project description

EPFL Center for Imaging logo

🐭 Mousetumorpy

A toolbox to segment and track murine lung tumor nodules in mice CT scans.

Hightlights

  • Lungs cavity identification: Run a pretrained YoloV8 model to segment the lungs and crop the CT scans around them.
  • 3D tumor nodules segmentation: Run a pretrained nnUNet model to segment tumor nodules in the lungs.
  • 3D tracking of tumor nodules: Track tumor nodules across CT scans acquired at different times.

Installation

Install the mousetumorpy package with pip:

pip install git+https://github.com/EPFL-Center-for-Imaging/mousetumorpy.git

or clone the project and install the development version:

git clone https://github.com/EPFL-Center-for-Imaging/mousetumorpy.git
cd mousetumorpy
pip install -e .

Usage as a CLI

The command-line interface (CLI) provides several image processing functions.

Crop

Run a YoloV8 model to segment the lungs cavity and crop the image around the lungs.

mousetumorpy crop <image_file> <out_dir>

For more details, see mousetumorpy crop --help.

Predict

Run a nnUNet model to segment tumor nodules.

mousetumorpy predict <image_file> <out_dir>

For more details, see mousetumorpy predict --help.

Combine

Combine several 3D images (ZYX) into a single 4D image (TZYX).

mousetumorpy combine <image_1> <image_2> <image_3> <out_dir>

For more details, see mousetumorpy combine --help.

Track

Track tumor nodules across a 4D mask (TZYX) time series using trackpy or laptrack.

mousetumorpy track <labels_file> <out_dir>

For more details, see mousetumorpy track --help.

License

This project is licensed under the AGPL-3 license.

This project depends on the ultralytics package which is licensed under AGPL-3.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

mousetumorpy-0.0.2.tar.gz (50.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

mousetumorpy-0.0.2-py3-none-any.whl (39.9 kB view details)

Uploaded Python 3

File details

Details for the file mousetumorpy-0.0.2.tar.gz.

File metadata

  • Download URL: mousetumorpy-0.0.2.tar.gz
  • Upload date:
  • Size: 50.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.22

File hashes

Hashes for mousetumorpy-0.0.2.tar.gz
Algorithm Hash digest
SHA256 eba34196a4bc284257d4eea406b620d0c5d482b9bfb23872a6dd4da22f9b32d2
MD5 5319780c25ec8ad7215fb19e24c28b4f
BLAKE2b-256 93aaffb4278160ffa59a80e81e34fb22389bc15cb036d1d06951749cd565de5d

See more details on using hashes here.

File details

Details for the file mousetumorpy-0.0.2-py3-none-any.whl.

File metadata

  • Download URL: mousetumorpy-0.0.2-py3-none-any.whl
  • Upload date:
  • Size: 39.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.22

File hashes

Hashes for mousetumorpy-0.0.2-py3-none-any.whl
Algorithm Hash digest
SHA256 d99628ce4127297f071174844ea8abedb76509776b303c2b93624b9d43702869
MD5 d70c16fc9a9459b1f0de1c1c8c33b177
BLAKE2b-256 139eb65380cdb1af456e41e55093f8707e25f44f8f5b8c71a921ec08e972d199

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page