Difference between revisions of "Events:Registration Summit August 2009"
From NAMIC Wiki
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== In-house evaluations of registration tools == | == In-house evaluations of registration tools == | ||
+ | * [http://www.na-mic.org/Wiki/index.php/Projects:DBP2:Harvard:Registration_Documentation Sophisticated end-user without computer vision background] | ||
* [http://www.na-mic.org/Wiki/index.php/Vervet_MRI_registration Vervet head MRI atlas-to-subject registration] | * [http://www.na-mic.org/Wiki/index.php/Vervet_MRI_registration Vervet head MRI atlas-to-subject registration] | ||
* [http://www.na-mic.org/Wiki/index.php/MeningiomaMRIRegistrationStudy Head MRI registration between different timepoints (human subjects, changing pathology present)] | * [http://www.na-mic.org/Wiki/index.php/MeningiomaMRIRegistrationStudy Head MRI registration between different timepoints (human subjects, changing pathology present)] |
Revision as of 03:02, 21 August 2009
Home < Events:Registration Summit August 2009Contents
Agenda
- Attendees: Casey Goodlett, Steve Pieper, Dominik Meier, Andriy Fedorov, Ron Kikinis
- Date and place: Friday, August 21, 1249 Boylston, 2nd floor conference room
- Schedule
- 09:00-12:00 Review of registration in Slicer:
- What input is the user asked to provide and in what form.
- Does a standard user understand what they are supposed to provide?
- What does the user expect registration results to look like?
- Bias correction
- histogram normalization
- handling image distortion (EPI)
- capture range and start pose
- ROI/VOI
- greyscale versus segmentation (binaries, surface models)
- List of modules:
- transformation module
- linear registration
- rigid registration
- affine registration
- b-spline registration
- register images
- Utah b-spline
- VMTK/Python ICP
- ACPC registration
- 12:00-01:00 Lunch
- 01:00-05:00 Making plans, use case scenarios, sample data sets, plan larger registration summit
Other items:
- Workflow with Wendy
- CUDA Implementation with Yogesh
Needs
- Robust solutions
- Clinical APIs as opposed to engineering APIs
- Good default parameters
- Modality recorded in the image class to automate use case and parameter selection
- Fast techniques for interactive investigations
- Non-interactive techniques can run longer
- Transform IO to all modules (mapping RAS to LPS as needed)
- Ability to apply estimated transforms to other types of data
- Region of interest registration (anything from a brain mask to a structure segmentation)
- Validation datasets
- Regression testing of registration accuracy
References
Bundled Registration and Tests
- http://www.slicer.org/slicerWiki/index.php/Documentation-3.4#Registration
- http://www.na-mic.org/Wiki/index.php/Projects:DBP2:Harvard:Registration_Documentation
- http://www.na-mic.org/Wiki/index.php/MeningiomaMRIRegistrationStudy#Limitations_of_the_Slicer_registration_tools
Some Sample data
Slicer-compatible add-on registration modules
- http://www.bioimagesuite.org/
- http://www.nitrc.org/frs/shownotes.php?release_id=575
- http://www.nitrc.org/projects/multimodereg/
- http://www.nitrc.org/projects/brainsmush/
- http://www.nitrc.org/projects/brainsdemonwarp/
- http://www.nitrc.org/projects/cmtk/