Quanfima: An open source Python package for automated fiber analysis of biomaterials

Area of Science:

• Biomaterials Science
• Computational Biology
• Medical Imaging

Background:

• Hybrid 3D scaffolds with fibrous structures and microparticles enhance cell integration and regeneration.
• Analyzing fiber characteristics in 3D hybrid biomaterials is challenging due to varying diameters and compositions.
• Existing biomaterial processing workflows lack integrated software for fiber analysis.

Purpose of the Study:

• To develop a Python package for comprehensive analysis of hybrid biomaterials.
• To enable accurate determination of fiber orientation, diameter, and porosity in 3D scaffolds.
• To provide a tool compatible with reproducible science workflows using Jupyter notebooks.

Main Methods:

• Development of the Python package 'quanfima' utilizing a tensor-based approach.
• Evaluation of the package on generated datasets with varying noise conditions.
• Application of quanfima to X-ray tomography datasets of diverse 3D scaffolds.

Main Results:

• The quanfima package accurately determines fiber orientation, fiber/particle diameter, and porosity.
• The tensor-based approach demonstrated high accuracy and performance across different datasets.
• Successful application to scaffolds for bone tissue engineering and pancreatic cell culturing.

Conclusions:

• quanfima offers a robust and accurate solution for analyzing complex hybrid biomaterials.
• The package facilitates reproducible research in biomaterials science and tissue engineering.
• This tool addresses the need for integrated fiber analysis in biomaterial processing workflows.