Difference between revisions of "2015 Summer Project Week:LinearFeatureRegistration"
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==Key Investigators== | ==Key Investigators== | ||
* Matthew Holden | * Matthew Holden | ||
| + | * Nicole Aucoin, BWH (fiducials) | ||
| + | * Eugenio Marinetto, UC3M Madrid (Line-Based Registration, Reg. Algorithm) | ||
==Project Description== | ==Project Description== | ||
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<h3>Progress</h3> | <h3>Progress</h3> | ||
* See: [https://github.com/mholden8/LinearObjectRegistration LinearObjectRegistration] | * See: [https://github.com/mholden8/LinearObjectRegistration LinearObjectRegistration] | ||
| + | * Discussed generic module for collecting/defining/acquiring parametric features: | ||
| + | ** Use data structure to store a set of 0D/1D/2D parametric features | ||
| + | ** For each feature, store raw point data, as well as basic information (i.e. centroid, variance, etc.) | ||
| + | ** Individual registration algorithms are implemented as modules using the data structure | ||
| + | ** Individual algorithm is responsible for converting 0D/1D/2D data to points/lines/planes (if applicable) | ||
| + | ** Methods for acquisition: tracking, models, fiducials, segmentation | ||
| + | * Use cases: | ||
| + | ** Phantom registration for ultrasound calibration | ||
| + | ** Line feature based image to tracker registration | ||
| + | ** Fiducial frame registration | ||
| + | * Began implementation of generic parametric features | ||
</div> | </div> | ||
</div> | </div> | ||
Latest revision as of 14:46, 24 June 2015
Home < 2015 Summer Project Week:LinearFeatureRegistration
Screenshot of LinearFeatureRegistration module
Key Investigators
- Matthew Holden
- Nicole Aucoin, BWH (fiducials)
- Eugenio Marinetto, UC3M Madrid (Line-Based Registration, Reg. Algorithm)
Project Description
Objective
- Add module for registration using linear features
Approach, Plan
- Investigate module use cases:
- Ultrasound calibration for PLUS
- ...
- Use Fiducial Registration Wizard module as a template
- Investigate whether linear features can be treated in the same way as fiducials
Progress
- See: LinearObjectRegistration
- Discussed generic module for collecting/defining/acquiring parametric features:
- Use data structure to store a set of 0D/1D/2D parametric features
- For each feature, store raw point data, as well as basic information (i.e. centroid, variance, etc.)
- Individual registration algorithms are implemented as modules using the data structure
- Individual algorithm is responsible for converting 0D/1D/2D data to points/lines/planes (if applicable)
- Methods for acquisition: tracking, models, fiducials, segmentation
- Use cases:
- Phantom registration for ultrasound calibration
- Line feature based image to tracker registration
- Fiducial frame registration
- Began implementation of generic parametric features
