Donut-like Object segmeNtation Utilizing Topological Data Analysis
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.
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