GoodFibes: An R Package for The Detection of Muscle Fibers from diceCT Scans.

Area of Science:

• Comparative anatomy
• Functional morphology
• Bioimaging

Background:

• Diffusible iodine-based contrast-enhanced computed tomography (diceCT) provides detailed, non-destructive muscle architecture data.
• Manual segmentation of muscle fibers is labor-intensive, and existing automated methods can be inaccessible or costly.

Purpose of the Study:

• To introduce GoodFibes, an open-source R package for 3D muscle architecture reconstruction from diceCT image stacks.
• To provide an accessible and affordable automated solution for muscle fiber analysis.

Main Methods:

• GoodFibes utilizes textural analysis of image grayscale values to track muscle fiber paths in 3D.
• The package includes functions for quality checking, fiber merging, and 3D visualization and export.
• Demonstrated utility with diceCT scans from ant and bat specimens.

Main Results:

• GoodFibes provides reliable measurements of mean fiber length, comparable to traditional methods.
• The software's effectiveness is on par with existing specialized packages.
• Successful reconstruction and analysis of muscle architecture in diverse datasets.

Conclusions:

• GoodFibes enhances accessibility to muscle fiber anatomy analysis using diceCT.
• The R package facilitates comparative and evolutionary studies by enabling direct statistical analysis of fiber metrics.
• Promotes wider adoption of diceCT in functional morphology research.