Registration of Bones Across Positions: Difference between revisions
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The geometrical model obtained from the neutral CT scans and the classification results are used to retrieve bone kinematics across positions. The model is registered in a given non-neutral position by searching until distance field similarity is maximized. | The geometrical model obtained from the neutral CT scans and the classification results are used to retrieve bone kinematics across positions. The model is registered in a given non-neutral position by searching until distance field similarity is maximized. | ||
==Technical Note== | |||
To run the classification and registration process, follow these steps: | |||
#check whether a "crop_values.txt" file exists-- it helps reduce the number of voxes processed | |||
#cd to the top-level of your subject's data | |||
#run $G/src/jspBin/batchGen.pl (this generates the files "unixbatch", "regbatch", "subsetbatch" in that directory) | |||
##The first time you process the data, accept all the defaults | |||
#ssh to a CS-LAB machine, e.g., "ssh cslab9g" | |||
#cd to the subject's root directory again | |||
#type "./unixbatch" | |||
The first pass often fails and you need to use the Wrist Viewer program to find a good initial position for the bone alignments that failed. This manually-found initial position information goes into files called "config_01L.ini", for example, and should be saved into the subject's root data directory. | |||
Repeat the process above and it should succeed this time. | |||
Revision as of 18:40, 2 June 2009
The registration process uses bone surfaces extracted from the neutral position and CT volumes to calculate bone kinematics, i.e rotations and translations of the center of mass of each each bone, across each position. This method has 2 steps.
Tissue Classification and Localized Distance Fields
Bone, soft tissue, and air are represented by different intensities in CT images. Our tissue classification algorithm goes thought the non-neutral CT volumes and calculates a distance from the center of each voxel to the closest material boundary. The output of classification is a distance field for each material. We are interested only in the distance field of the bone material.
Object Tracking
The geometrical model obtained from the neutral CT scans and the classification results are used to retrieve bone kinematics across positions. The model is registered in a given non-neutral position by searching until distance field similarity is maximized.
Technical Note
To run the classification and registration process, follow these steps:
- check whether a "crop_values.txt" file exists-- it helps reduce the number of voxes processed
- cd to the top-level of your subject's data
- run $G/src/jspBin/batchGen.pl (this generates the files "unixbatch", "regbatch", "subsetbatch" in that directory)
- The first time you process the data, accept all the defaults
- ssh to a CS-LAB machine, e.g., "ssh cslab9g"
- cd to the subject's root directory again
- type "./unixbatch"
The first pass often fails and you need to use the Wrist Viewer program to find a good initial position for the bone alignments that failed. This manually-found initial position information goes into files called "config_01L.ini", for example, and should be saved into the subject's root data directory.
Repeat the process above and it should succeed this time.