This Bone Analysis tutorial provides step-by-step instructions for pre-processing a dataset of a femoral head, segmenting the bone, and computing vector field maps of anisotropy. Additional topics in this tutorial describe how to visualize and evaluate the generated vector fields.
Screen capture of completed tutorial
Before you start the tutorial, you should download and unzip the tutorial dataset — Femoral Head. This dataset, as well as the session file of the tutorial, is available on the ORS website at: http://www.theobjects.com/dragonfly/learn-sample-datasets.html.
The pre-processing steps required to prepare the dataset, which include aligning the dataset with the anatomical axes and cropping the derived dataset from the re-oriented view, are described in this section.
The dataset appears in the Data Properties and Settings panel.



The Translate and Rotate tools appear in the selected view.
NOTE You can use the Rotate and Translate tools in any MPR view of the dataset (see Moving, Rotating, and Scaling Objects).
The derived dataset appears in the Data Properties and Settings panel when the computation is complete.
The Dataset Cropper panel appears on the Dataset Tools tab on the right sidebar and a clip box appears in the views of the dataset.

NOTE You can choose to apply cropping directly to the dataset or to create a new dataset.
In this section, you will learn how to extract the required region of interest from a threshold range applied to the image data. Instructions for refining the initial segmentation are also included here.
See Scene Layouts and Views for information about changing layouts).
The ROI Tools panel appears on the left sidebar.



A new region of interest is added to the Data Properties and Settings panel. Information about the new ROI is displayed in the lower section of the panel (see ROI Properties and Settings).

All unconnected objects that are smaller than the largest object in the region of interest are removed from the ROI (see Processing Islands).
NOTE With this initial bone segmentation you can separate the cortical shell from the trabecular interior automatically and then compute morphometric indices (see Computing Cortical and Trabecular Measurements). Other options include creating a graph for topological analysis (see Graphing Regions of Interest), exporting the ROI as a binary image (see ROI as Binary), closing holes for 3D print preparation (see Close Holes Smaller Than), and creating a distance map for other analysis purposed (see Creating Distance Maps).
This section provides step-by-step instructions for computing a 3D vector field-based map of anisotropy.

A new Box shape appears in the Data Properties and Settings panel. Click the Eye icon to show the box in the workspace views.

You can resize and rotate the box, as well as change its position within a 2D or 3D view with the control points (see Editing Shapes).
NOTE Large box sizes and small spacing and/or radius of influence settings will increase computation time.


NOTE Although the highest resolution, or lowest spacing, is 0.085 mm, this is increased to reduce processing times as the entire 3D shape of the femoral head will be mapped.
NOTE The radius of influence defines the kernel size, or elementary volume, within which anisotropy will be evaluated. You should note that a too small radius of influence may result in a low signal-to-noise ratio, while a too high radius can result in averaging and edge effects.


This will map the anisotropy of 3D surfaces — their preferred orientation between 0 (random) and 1 (perfectly aligned) and the direction of that preferred orientation with respect to the Cartesian coordinates.
Two new items — a vector field and scalar-based anisotropy dataset — appear in the Data Properties and Settings panel after all computations are complete.

This section describes the different settings that can be applied to the vector field-based anisotropy map that was computed in this tutorial.
In the examples below, the top row corresponds to the anterior view, while the bottom row provides views of the posterior aspect. The images on the top left shows the relationship between the box and the 3D rendering of the femoral head at the default settings. The images in the middle show anisotropy mapped by magnitude, with red being very anisotropic and blue very isotropic. The images on the right show the same maps replotted in such a way that the color corresponds to the vector orientation. This is case, red is along the X axis, green is along the Y axis, and blue is along the Z axis.
Vector field-based maps of anisotropy
The properties and settings for the 3D vector field appear in the bottom section of the Data Properties and Settings panel.
The 3D vector field-based anisotropy map appears in the 3D view at the default settings, with the vectors corresponding to the highest surface anisotropy colored yellow and those corresponding to the lowest , or isotropy, colored blue..
Information and settings related to the 3D vector fields appear in the bottom section of the Data Properties and Settings panel.

NOTE In most cases, you should hide the rendering of the dataset if it is visible in the 3D view.


NOTE The Jet LUT is often a good color scheme choice. In this LUT, vectors corresponding to the highest surface anisotropy are colored red, while those corresponding to the lowest, or are isotropic, are colored blue.

Checking this option will re-code the vector map in accordance with the orientation of the vectors — red for the X axis, green for the Y axis, and blue for the Z axis.
These options are described in the tutorial Anisotropy and Volume Fraction Mapping of a Proximal Femur.