Welcome to BoneJ Headless Documentation!

Microstructure metrics are calculated to characterize bone morphology and skeletal geometry. BoneJ is a Fiji plugin for calculation of microstructure metrics and bone analysis with unique plugins not available from vendors. The plugins can be automated with simple Fiji macros, but this still requires GUI support. This repository allows for automation of BoneJ in Python without GUI dependence and can allow for quick processing of large datasets, access to Python libraries, and a simple method of parameter sweeping to optimize BoneJ plugins. This repository was used to analyze several microCT images and compared microstructure metrics from other sources. All scripts are written in Python and can only be executed on Linux OS.

Table of Contents

• Installation
  • Requirements
  • Installation
  • Usage
• Primary Plugins
  • Thickness
  • Spacing
  • Anisotropy
  • Connectivity
  • Bone Volume Fraction
  • Ellipsoid Factor
• Secondary Plugins
  • Surface Area
  • Skeletonise
  • Analzye Skeleton
  • Fractal Dimension
  • Intertrabecular Angles
• Examples
  • BoneJ Module
  • BoneJ Secondary Module
  • Anisotropy Parameter Convergence
  • Ellipsoid Factor Convergence

Plugins

Currently supports the following plugins:

• Trabecular Thickness

• Trabecular Spacing

• Anisotropy

• Area Volume Fraction

• Connectivity

• Ellipsoid Factor

Secondary plugins:

• Surface Area

• Fractal Dimension

• Skeletonise

• Analyze Skeleton

• Intertrabecular Angles

Detailed description on individual plugins is provided in section plugins.

Installation

Fiji can be installed with the following link:

• https://imagej.net/software/fiji/downloads

For more detailed installation instructions for BoneJ, see https://imagej.net/plugins/bonej.

BoneJ Headless Team: Harsha Marupudi, Qian Cao, Ravi Samala, Nicholas Petrick

Citations:

Bouxsein, Mary L, Stephen K Boyd, Blaine A Christiansen, Robert E Guldberg, Karl J Jepsen, and Ralph Müller. “Guidelines for Assessment of Bone Microstructure in Rodents Using Micro-Computed Tomography.” Journal of Bone and Mineral Research 25, no. 7 (June 7, 2010): 1468–86. https://doi.org/10.1002/jbmr.141.

Domander, Richard, Alessandro A Felder, and Michael Doube. “BoneJ2 - Refactoring Established Research Software.” Wellcome Open Research 6 (February 22, 2021): 37. https://doi.org/10.12688/wellcomeopenres.16619.1.

Doube, Michael, Michał M. Kłosowski, Ignacio Arganda-Carreras, Fabrice P. Cordelières, Robert P. Dougherty, Jonathan S. Jackson, Benjamin Schmid, John R. Hutchinson, and Sandra J. Shefelbine. “BoneJ: Free and Extensible Bone Image Analysis in ImageJ.” Bone 47, no. 6 (December 2010): 1076–79. https://doi.org/10.1016/j.bone.2010.08.023. Felder, A A, S Monzem, R De Souza, B Javaheri, D Mills, A Boyde, and M Doube. “The Plate-to-Rod Transition in Trabecular Bone Loss Is Elusive,” n.d., 18.

Doube M, Kłosowski MM, Arganda-Carreras I, Cordeliéres F, Dougherty RP, Jackson J, Schmid B, Hutchinson JR, Shefelbine SJ. BoneJ: free and extensible bone image analysis in ImageJ. Bone 47 1076-1079 (2010). doi: 10.1016/j.bone.2010.08.023

Dougherty R, Kunzelmann K (2007), Computing local thickness of 3D structures with ImageJ, Microsc. Microanal., 13: 1678-1679, <doi:10.1017/S1431927607074430>

Hildebrand T, Rüegsegger P (1997), A new method for the model-independent assessment of thickness in three-dimensional images, J. Microsc., 185: 67-75, <doi:10.1046/j.1365-2818.1997.1340694.x>

Odgaard A (1997), Three-dimensional methods for quantification of cancellous bone architecture, Bone, 20, 315-328, <doi:10.1016/S8756-3282(97)00007-0>

Harrigan TP, Mann RW (1984), Characterization of microstructural anisotropy in orthotropic materials using a second rank tensor, J Mater Sci, 19, 761-767, <doi:10.1007/BF00540446>

Odgaard A, Gundersen HJG (1993), Quantification of connectivity in cancellous bone, with special emphasis on 3-D reconstructions, Bone 14: 173-182, <doi:10.1016/8756-3282(93)90245-6>.

Toriwaki J, Yonekura T (2002), Euler number and connectivity indexes of a three dimensional digital picture, Forma 17: 183-209 Rasband, W.S., ImageJ, U. S. National Institutes of Health, Bethesda, Maryland, USA, https://imagej.nih.gov/ij/, 1997-2018.