Fourier transform-based method for quantifying the three-dimensional orientation distribution of fibrous units

Area of Science:

• Materials Science
• Biophysics
• Image Analysis

Background:

• Many materials and biological tissues feature fibrous microstructures within a matrix.
• Understanding fiber orientation distribution is crucial for predicting material properties.

Purpose of the Study:

• To present a novel 3D Fourier transform-based method for quantifying fiber orientation distribution.
• To enable accurate identification of fiber families and their dispersion (in-plane and out-of-plane).

Main Methods:

• Developed a 3D Fourier transform algorithm for fiber orientation analysis.
• Validated the method using artificial 3D images with known fiber distributions.
• Assessed accuracy by comparing reconstructed and prescribed fiber dispersion.
• Tested robustness using fiber density measures.
• Applied the method to in vitro second harmonic generation microscopy data of skin collagen fibers.

Main Results:

• The novel method accurately quantifies fiber orientation and dispersion in 3D.
• Demonstrated fast computation times for the analysis.
• Successfully reconstructed collagen fiber orientation distributions in human and mouse skin.
• Validated the method's accuracy and robustness against artificial and real-world data.

Conclusions:

• The developed 3D Fourier transform method provides a robust and efficient tool for analyzing fibrous microstructures.
• Quantified fiber dispersion parameters can enhance mechanical models for soft tissues and fiber-reinforced materials.
• The technique offers insights into the complex architecture of biological tissues like skin.