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XROMM
  • Table of Contents
  • Introduction to XROMM
  • Model Generation
    • Model Generation: Creating 3D models using Amira software
    • Model Generation : Creating 3D models with Horos
    • Model Generation : Creating 3D models with 3D Slicer
    • Model Generation : 3D Marker Models with Horos
    • Model Generation : Cleaning up 3D models with Geomagic
    • Model Generation : Cleaning 3D models with MeshLab
    • Model Generation : Measure CT Marker Coordinates in Maya
  • Animate Bones and Markers
    • Animate Bones and Markers : Importing mesh models into Maya from Horos
    • Animate Bones and Markers : Animate Bones in Maya
    • Animate Bones and Markers : Check Your Animation with MayaCams
  • Maya Analysis and Visualization
    • Maya Analysis and Visualization : Working with joint coordinate systems (JCS)
    • Maya Analysis and Visualization : Measuring and exporting the distance between two points
    • Maya Analysis and Visualization : Measuring XYZ Coordinates of a Point Over Time
    • Maya Analysis and Visualization : Parent a camera to a reference bone
    • Maya Analysis and Visualization : Relative Motion
  • Scientific Rotoscoping
    • Scientific Rotoscoping : Recreate X-Ray cameras in Maya
    • Scientific Rotoscoping : Scientific Rotoscoping in Maya
      • Scientific Rotoscoping : Pan and Scan tools for Rotoscoping
    • Scientific Rotoscoping : Animating a Bone with One or Two Markers
  • Tips and Tools
    • Tips and Tools : Open Maya files from a newer version with older versions
    • Tips and Tools : Precision testing using frozen cadavers
    • Tips and Tools : Import XYZ points into Maya
  • XMAPortal User Manual
    • XMAPortal : Getting Started with XMAPortal
    • XMAPortal : How to Create a New Study
    • XROMM : How to Modify Study Metadata
    • XROMM : How to give access or revoke access to see your study
    • XMAPortal : Data Organization
    • XMAPortal : Metadata Pool
    • XMAPortal : How to Create Trials
    • XMAPortal : How to edit an existing trial
    • XMAPortal : How to upload files
      • XMAPortal : Clearing your browser history
      • XMAPortal : Changing how Java applet connects to the network
      • XMAPortal : Show Firefox developer window
    • XMAPortal : Hide Files
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  • Example data set
  • Frozen Pig Head

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  1. Tips and Tools

Tips and Tools : Precision testing using frozen cadavers

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Last updated 5 years ago

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The precision of an XROMM study can be quantified by substituting a frozen specimen for the live subject in the workflow. This method is study-specific and should be repeated for each XROMM study conducted.

A frozen specimen is mounted to a substrate that is not radiopaque (e.g. a wooden pole) and then moved in three dimensions within the biplanar x-ray field. Joints in a frozen specimen should be immovable and thus by default all relative motions between markers and bones, respectively, should be zero. The amount of deviation from zero is the measurement of precision.

The current method quantifies precision using standard deviations of the resulting intermarker distance and the 6 DOF data (translations and rotations of joints). Movements recorded in live subjects that fall below these standard deviations should be considered error or “noise” and not interpreted as real joint motions. The following examples demonstrate precision measurements in various XROMM studies.

Example data set

Frozen Pig Head

The frozen pig specimen had a total of 9 markers: 1-4 in the skull and 5-9 in the mandible. Markers from 2 trials (1,000 frames/trial) were digitized and standard deviations of intermarker distances calculated.

Rigid body kinematics were calculated from digitized marker XYZ coordinates and used to animate bone movements. A joint coordinate system (JCS) was set for the pig mandible using the mandibular condyles to align the JCS. 6 DOF data was generated from this JCS and standard deviations were calculated for each aspect of joint translation and rotation.

The results of this precision study can then be applied to 6 DOF data in order to distinguish noise from real movements. Here, error envelopes have been added to a chart of mandibular rigid body translations during pig chewing. The error envelopes are calculated as the mean of the translational movements (for this frame subset) +/- the SD for that translation as calculated in the precision study. For example: the mean of T(X) in these frames +/- precision study SD for T(X) = 0.190 +/- 0.005 cm.