Difference between revisions of "Modules:PythonSurfaceICPRegistration-Documentation-3.4"
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===Module Name=== | ===Module Name=== | ||
| − | + | Python ICP Registration | |
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== General Information == | == General Information == | ||
===Module Type & Category=== | ===Module Type & Category=== | ||
| − | Type: | + | Type: CLI |
| − | Category: | + | Category: Surface Models |
===Authors, Collaborators & Contact=== | ===Authors, Collaborators & Contact=== | ||
| − | * | + | * Luca Antiga: Mario Negri Institute |
| − | + | * Daniel Blezek: Mayo Clinic | |
| − | * | + | * Contact: Luca Antiga, antiga@marionegri.it |
| − | * Contact: | ||
===Module Description=== | ===Module Description=== | ||
| − | + | This Python module registers an input surface to a target surface using the Iterative Closest Point algorithm using rigid, similarity and affine transforms. | |
== Usage == | == Usage == | ||
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===Examples, Use Cases & Tutorials=== | ===Examples, Use Cases & Tutorials=== | ||
| − | * | + | * The module is appropriate when there is need for aligning surfaces, e.g. for comparison of surface features. |
| − | * | + | * Possible improvements are the generation of the registration transform in output (TO DO). |
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===Quick Tour of Features and Use=== | ===Quick Tour of Features and Use=== | ||
List all the panels in your interface, their features, what they mean, and how to use them. For instance: | List all the panels in your interface, their features, what they mean, and how to use them. For instance: | ||
| − | * ''' | + | * '''Surface ICP Registration Parameters:''' |
| − | * ''' | + | ** ''Landmark transform mode'': choose between RigidBody, Similarity or Affine transforms for registration of the surfaces. |
| − | * ''' | + | ** ''Mean distance mode'': choose between square root of the average of the sum of squares of the closest point distances (RMS) or mean of the sum of absolute values of the closest point distances (Absolute) |
| − | * ''' | + | ** ''Maximum number of iterations'': number of iterations beyond which the ICP algorithm won't proceed even if the maximum mean distance is above threshold. |
| + | ** ''Maximum number of landmarks'': maximum number of surface landmarks used to minimize distance between surfaces | ||
| + | ** ''Start by matching centroids'': initialize the transform by translating the input surface so that its centroid coincides the centroid of the target surface. | ||
| + | ** ''Check mean distance'': force checking distance between every two iterations (slower but more accurate) | ||
| + | ** ''Maximum mean distance'': distance threshold, the algorithm stops when the mean distance between the surfaces is below this threshold | ||
| + | * '''IO:''' | ||
| + | ** ''Input Surface'': the input (moving) surface | ||
| + | ** ''Target Surface'': the target (not moving) surface | ||
| + | ** ''Output Surface'': the input surface registered on the target surface | ||
== Development == | == Development == | ||
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===Dependencies=== | ===Dependencies=== | ||
| − | + | Python | |
===Known bugs=== | ===Known bugs=== | ||
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===Source code & documentation=== | ===Source code & documentation=== | ||
| − | + | Follow this [http://viewvc.slicer.org/viewcvs.cgi/trunk/Modules/Python/ link] to the module. | |
[http://www.na-mic.org/Slicer/Documentation/Slicer3/html/ Links] to documentation generated by doxygen. | [http://www.na-mic.org/Slicer/Documentation/Slicer3/html/ Links] to documentation generated by doxygen. | ||
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===Acknowledgment=== | ===Acknowledgment=== | ||
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===References=== | ===References=== | ||
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| + | [http://www.vtk.org/doc/nightly/html/classvtkIterativeClosestPointTransform.html vtkIterativeClosestPointTransform] | ||
Revision as of 10:08, 11 February 2009
Home < Modules:PythonSurfaceICPRegistration-Documentation-3.4Return to Slicer 3.4 Documentation
Module Name
Python ICP Registration
General Information
Module Type & Category
Type: CLI
Category: Surface Models
Authors, Collaborators & Contact
- Luca Antiga: Mario Negri Institute
- Daniel Blezek: Mayo Clinic
- Contact: Luca Antiga, antiga@marionegri.it
Module Description
This Python module registers an input surface to a target surface using the Iterative Closest Point algorithm using rigid, similarity and affine transforms.
Usage
Examples, Use Cases & Tutorials
- The module is appropriate when there is need for aligning surfaces, e.g. for comparison of surface features.
- Possible improvements are the generation of the registration transform in output (TO DO).
Quick Tour of Features and Use
List all the panels in your interface, their features, what they mean, and how to use them. For instance:
- Surface ICP Registration Parameters:
- Landmark transform mode: choose between RigidBody, Similarity or Affine transforms for registration of the surfaces.
- Mean distance mode: choose between square root of the average of the sum of squares of the closest point distances (RMS) or mean of the sum of absolute values of the closest point distances (Absolute)
- Maximum number of iterations: number of iterations beyond which the ICP algorithm won't proceed even if the maximum mean distance is above threshold.
- Maximum number of landmarks: maximum number of surface landmarks used to minimize distance between surfaces
- Start by matching centroids: initialize the transform by translating the input surface so that its centroid coincides the centroid of the target surface.
- Check mean distance: force checking distance between every two iterations (slower but more accurate)
- Maximum mean distance: distance threshold, the algorithm stops when the mean distance between the surfaces is below this threshold
- IO:
- Input Surface: the input (moving) surface
- Target Surface: the target (not moving) surface
- Output Surface: the input surface registered on the target surface
Development
Dependencies
Python
Known bugs
Follow this link to the Slicer3 bug tracker.
Usability issues
Follow this link to the Slicer3 bug tracker. Please select the usability issue category when browsing or contributing.
Source code & documentation
Follow this link to the module.
Links to documentation generated by doxygen.
