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Automated Multi-Scale Morphometry Analysis of Fibrous Networks
Sandesh Giri1, Kenneth Gordon2, Karson Vidrine1
1Department of Mechanical Engineering, University of Louisiana at Lafayette, Lafayette, Louisiana 70503, United States.
ACS Omega
|April 6, 2026
Summary
A new automated Fiber Analyzer GUI accurately quantifies complex fibrous materials. This tool overcomes limitations in traditional methods for analyzing fiber networks in diverse applications.
Area of Science:
- Materials Science
- Image Analysis
- Biotechnology
Background:
- Fibrous materials are crucial in medicine, energy, textiles, and composites.
- Analyzing fibrous structures in microscopy images is challenging due to intertwined fibers and mixed components.
- Existing methods are often inaccurate, subjective, and time-consuming.
Purpose of the Study:
- To develop a novel automated framework for quantitative morphometric analysis of fibrous materials.
- To address limitations in characterizing complex fiber-particle networks.
- To provide an accessible, accurate, and reproducible tool for researchers.
Main Methods:
- Developed an interactive Fiber Analyzer GUI with a dual-pipeline discriminator.
- Implemented a filter-based approach and morphological filtering with aspect-ratio thresholding.
- Utilized Adaptive Contour-based Diameter Estimation (ACDE) with active contour models.
Main Results:
- Achieved efficient implementation times (19-25 s per ROI).
- Demonstrated significantly reduced error rates (mean error 7.17% ± 1.29%) for pure and mixed samples.
- Validated performance on complex fibrous networks with varying fiber diameters and particulate matter.
Conclusions:
- The Fiber Analyzer GUI offers accurate and reproducible quantification of complex fibrous networks.
- This automated framework overcomes challenges in traditional image analysis for fibrous materials.
- The tool is freely accessible, advancing morphometric analysis in diverse scientific fields.
