Difference between revisions of "Registration:Categories"
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[http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:UseCaseInventory '''Slicer Registration Case Library''': Examples & Tutorials] | [http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:UseCaseInventory '''Slicer Registration Case Library''': Examples & Tutorials] | ||
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| − | + | = Speed [[Image:Registration_Speed_icon.png|70px]] = | |
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| − | = Precision [[Image:Registration_Precision_icon.png| | + | *'''Affine:''' The [[Modules:AffineRegistration-Documentation-3.4|'''Affine Registration''']] Module performs automated affine registration. This is being replaced by the [[Modules:RegisterImages-Documentation-3.4|Register Images]] Module that performs the same function. |
| − | *RegisterImages | + | *'''Bspline:''' The [[Modules:DeformableB-SplineRegistration-Documentation-3.4|'''Deformable B-Spline Registration''']] Module performs non-rigid automated image registration. |
| + | *'''Manual'''/interactive alignment can be done via the [[Modules:Transforms-Documentation-3.4|'''Transforms''' ]] module, e.g. for initial alignment. See [[Slicer3.4:Training#Slicer_3.4_Tutorials| here for a tutorial and example dataset on Manual Registration]] | ||
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| + | = Precision [[Image:Registration_Precision_icon.png| 70px]] = | ||
| + | *The [[Modules:RegisterImages-Documentation-3.4|'''Register Images''']] Module performs automated image registration, rigid to affine, based on image intensity similarities. It allows to focus the registration on a region of interest | ||
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= Robustness = | = Robustness = | ||
| − | * | + | *The [[Modules:RegisterImagesMultiRes-Documentation-3.6|'''Multires Registration''']] module performs robust automated affine image registration employing a multi-resolution scheme. |
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| − | = | + | = DOF [[Image:Registration_HLogo_DOF.png| 70px]] = |
| − | * | + | *'''rigid 6 DOF:''' |
| − | * | + | *'''similarity 9 DOF:''' |
| − | * | + | *'''affine 12 DOF:''' |
| − | * | + | *'''non rigid 27- 100s DOF:''' |
| + | *'''non rigid (fluid) >100 DOF''' The [[Modules:DemonsRegistration-Documentation-3.5|'''Demons Non-rigid Registration''' ]] Module performs automated registration of images based on an optic flow mechanism. Deformations here are significantly more "fluid" (i.e. have more DOF and are less constrained) than for the BSpline method. | ||
| + | = Datatype [[Image:Registration_HLogo_Datatype.png| 70px]] = | ||
| + | *'''images, same modality:''' The [[Modules:RegisterImages-Documentation-3.4|'''Register Images''']] Module performs automated image registration, rigid to affine, based on image intensity similarities. It allows to focus the registration on a region of interest | ||
| + | *'''images, different modality:''' The [[Modules:RegisterImages-Documentation-3.4|'''Register Images''']] Module performs automated image registration, rigid to affine, based on image intensity similarities. Select Mutual Information as cost function. | ||
| + | *'''surfaces:''' The [[Modules:PythonSurfaceICPRegistration-Documentation-3.4|'''ICP Surface Registration''' ]] Module performs automated registration of surfaces (not images). This is useful if image data directly is unreliable, but surfaces can be produced from segmentations that provide good information about desired alignment. | ||
| + | *'''fiducials:''' The [[Modules:FiducialRegistration |'''Fiducial Alignment''']] Module can align images based on pairs of manually selected fiducial points (rigid and affine). Two sets of fiducials (fiducial lists) are required, forming matching pairs to be aligned. See ''Fiducials'' module below. | ||
| − | = Brain [[Image:Registration_HLogo_Brain.png| | + | = Brain [[Image:Registration_HLogo_Brain.png| 70px]] = |
| − | * | + | *The [[Modules:RealignVolume-Documentation-3.4|'''ACPC Transform''']] Module is used to orient '''brain''' images along predefined anatomical landmarks: (manually defined) fiducials for the inter-hemispheral midline, anterior- and posterior commissure are used to align an image such that these landmarks become vertical and horizontal, respectively. |
*BrainsDemon | *BrainsDemon | ||
*BrainsMush | *BrainsMush | ||
| − | * | + | *The [http://na-mic.org/Wiki/index.php/2010_Winter_Project_Week_HAMMER '''HAMMER'''] Module performs elastic (non-rigid) alignment of '''brain''' images of different individuals based on tissue class segmentation and intensity (experimental stage). |
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Revision as of 22:31, 13 April 2010
Home < Registration:CategoriesBack to registration portal page
Slicer Registration Case Library: Examples & Tutorials
Contents
Speed 
- Affine: The Affine Registration Module performs automated affine registration. This is being replaced by the Register Images Module that performs the same function.
- Bspline: The Deformable B-Spline Registration Module performs non-rigid automated image registration.
- Manual/interactive alignment can be done via the Transforms module, e.g. for initial alignment. See here for a tutorial and example dataset on Manual Registration
Precision 
- The Register Images Module performs automated image registration, rigid to affine, based on image intensity similarities. It allows to focus the registration on a region of interest
Robustness
- The Multires Registration module performs robust automated affine image registration employing a multi-resolution scheme.
DOF 
- rigid 6 DOF:
- similarity 9 DOF:
- affine 12 DOF:
- non rigid 27- 100s DOF:
- non rigid (fluid) >100 DOF The Demons Non-rigid Registration Module performs automated registration of images based on an optic flow mechanism. Deformations here are significantly more "fluid" (i.e. have more DOF and are less constrained) than for the BSpline method.
Datatype 
- images, same modality: The Register Images Module performs automated image registration, rigid to affine, based on image intensity similarities. It allows to focus the registration on a region of interest
- images, different modality: The Register Images Module performs automated image registration, rigid to affine, based on image intensity similarities. Select Mutual Information as cost function.
- surfaces: The ICP Surface Registration Module performs automated registration of surfaces (not images). This is useful if image data directly is unreliable, but surfaces can be produced from segmentations that provide good information about desired alignment.
- fiducials: The Fiducial Alignment Module can align images based on pairs of manually selected fiducial points (rigid and affine). Two sets of fiducials (fiducial lists) are required, forming matching pairs to be aligned. See Fiducials module below.
Brain 
- The ACPC Transform Module is used to orient brain images along predefined anatomical landmarks: (manually defined) fiducials for the inter-hemispheral midline, anterior- and posterior commissure are used to align an image such that these landmarks become vertical and horizontal, respectively.
- BrainsDemon
- BrainsMush
- The HAMMER Module performs elastic (non-rigid) alignment of brain images of different individuals based on tissue class segmentation and intensity (experimental stage).
