A pipeline for Automated Lesion and Feature Extraction from brain MRIs
Project description
PyALFE
Python implementation of Automated Lesion and Feature Extraction (pyALFE) pipeline. We developed this pipeline for analysis of brain MRIs of patients suffering from conditions that cause brain lesions. It utilizes image processing tools, image registration tools, and deep learning segmentation models to produce a set of features that describe the lesions in the brain.
Documentation
Details about installation and usage can be found at: https://reghbali.github.io/pyalfe
To get started, you can go through this tutorial: https://reghbali.github.io/pyalfe/guides/tutorial.html
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Please make sure to update tests as appropriate.
License
BSD 3-Clause
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file pyalfe-0.1.1.tar.gz
.
File metadata
- Download URL: pyalfe-0.1.1.tar.gz
- Upload date:
- Size: 16.4 MB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | fa690ea917cef1d4812414ddb3b4fd7af94f558da64583843affeb5884bdcdef |
|
MD5 | 83b346bd9198e08130148df245a40371 |
|
BLAKE2b-256 | b1bfc51d877af7ed0157d388d4a87bfb5e55c786d9a701ab37f921ea0a96fc9b |
File details
Details for the file pyalfe-0.1.1-py3-none-any.whl
.
File metadata
- Download URL: pyalfe-0.1.1-py3-none-any.whl
- Upload date:
- Size: 16.4 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: twine/5.1.1 CPython/3.12.6
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | d8e4903054db4cecdc596ce0ce6d9b95286b6f07ba6e4931cc00944a334454ee |
|
MD5 | 1ae3a14e0f93d0ddf3b329307025b218 |
|
BLAKE2b-256 | 4400ec297b43edc0c375c3310293a0191e53a85e0e8e19ab7e9f7fb643c49175 |