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Fibril-associated Collagen

Fibril-associated Collagen

Fibril-associated collagens are a type of collagens present in the extracellular matrix with interrupted triple helices or FACIT (Fibril-associated collagens interrupted triple-helices). FACIT help connect and attach the collagen fibrils with each other as well as with other proteins of the extracellular matrix.
For example, the type II collagen fibrils in cartilage have covalently bound type IX fibril-associated collagens at regular intervals. Other types of fibril-associated collagens are...

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Updated: Feb 24, 2026

Quantifying Fibrillar Collagen Organization with Curvelet Transform-Based Tools

Quantifying Fibrillar Collagen Organization with Curvelet Transform-Based Tools

Published on: November 11, 2020

Methods for Quantifying Fibrillar Collagen Alignment.

Yuming Liu¹, Adib Keikhosravi^1,2, Guneet S Mehta^1,2

¹Laboratory for Optical and Computational Instrumentation, University of Wisconsin, Madison, WI, USA.

Methods in Molecular Biology (Clifton, N.J.)

|August 25, 2017

Summary

This summary is machine-generated.

A new open-source MATLAB software framework quantifies collagen fiber alignment in disease research. This tool analyzes individual fibers and their orientation relative to boundaries, improving disease diagnostics and research.

Keywords:

Cancer imaging Collagen alignment Collagen organization Collagen quantification Curvelet transform Extracellular matrix Fiber tracking Fibrillar collagen Second-harmonic generation microscopy Tumor-associated collagen signatures

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Last Updated: Feb 24, 2026

Quantifying Fibrillar Collagen Organization with Curvelet Transform-Based Tools

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Published on: November 11, 2020

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Production of Nanofibrillar Patterned Collagen for Tissue Engineering

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Published on: September 20, 2024

Area of Science:

Biomedical Engineering
Computational Biology
Materials Science

Background:

Fibrillar collagen's role in diseases like cancer and asthma is increasingly recognized.
Collagen fiber alignment is a key pathological indicator.
Current imaging analysis tools lack fiber-wise quantification and boundary-relative orientation.

Purpose of the Study:

To introduce a novel, open-source MATLAB software framework for quantifying collagen fiber alignment.
To provide a user-friendly tool for analyzing collagen organization in biological images.
To enable measurement of fiber orientation globally, within regions of interest, and relative to boundaries.

Main Methods:

Development of a MATLAB software framework with "CurveAlign" and "CT-FIRE" packages.
Utilizing an improved fiber tracking algorithm for individual fiber extraction.
Employing the curvelet transform for optimal fiber edge representation.

Main Results:

The software enables robust, fiber-wise quantification of collagen alignment.
Users can measure orientation globally, in specific regions, and relative to boundaries.
The framework is accessible to users without prior programming or image processing experience.

Conclusions:

This open-source tool significantly advances the quantitative analysis of collagen organization.
It facilitates a deeper understanding of collagen's role in various diseases.
The software promotes efficient and accurate collagen imaging data analysis.