Sentinal4D/cellshape
3D shape analysis using deep learning
This tool helps cell biologists and cancer researchers analyze the 3D shapes of individual cells, particularly cancer cells, from microscopy images. It takes 3D binary masks of cells or cell point clouds as input, then identifies key shape features and categorizes cells into distinct shape classes. This allows researchers to understand how cell shape changes due to treatments or conditions, without needing to manually define shape characteristics.
No commits in the last 6 months. Available on PyPI.
Use this if you need to quantify and classify complex 3D cell shapes from your microscopy data to understand biological processes or drug responses.
Not ideal if you are working with 2D images, need to analyze cellular substructures, or do not have access to GPU hardware for processing.
Stars
31
Forks
6
Language
Python
License
BSD-3-Clause
Category
Last pushed
Oct 08, 2025
Commits (30d)
0
Dependencies
13
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