Metadata-Version: 2.1
Name: donutda
Version: 1.0
Summary: Donut-like Object segmeNtation Utilizing Topological Data Analysis
Home-page: https://github.com/ulgenklc/DONUTDA
Author: Bengier Ulgen Kilic
Author-email: bengieru@buffalo.edu
License: MIT
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: eztda
Requires-Dist: numpy
Requires-Dist: matplotlib

# DONUTDA
A python based semi-supervised software for Donut-like Object segmeNtation Utilizing Topological Data Analysis.

DONUTDA implements persistent homology to perform image analysis on biomedical image data. Taking a 2d-grayscale image as an input, there are four easy steps for algorithm to spit out the desired masks of the regions of interest(ROI).

The GUI is available.


