Registration:Resampling - Revision history

Meier: /* Resampling via a spatial transform */

2010-05-18T14:56:32Z

Resampling via a spatial transform

Meier at 14:54, 18 May 2010

2010-05-18T14:54:55Z

Meier: /* Resampling Surface- and Model-Data */

2010-05-17T21:23:18Z

Resampling Surface- and Model-Data

Meier: /* Resampling Surface- and Model-Data */

2010-05-17T21:22:57Z

Resampling Surface- and Model-Data

Meier: /* Resampling Vector- and Tensor-Data */

2010-05-17T20:26:06Z

Resampling Vector- and Tensor-Data

Meier at 19:52, 17 May 2010

2010-05-17T19:52:58Z

Meier at 18:53, 17 May 2010

2010-05-17T18:53:07Z

Meier: /* What we mean by Resampling */

2010-05-17T15:19:47Z

What we mean by Resampling

Meier: /* Resampling via a spatial transform */

2010-05-17T14:24:48Z

Resampling via a spatial transform

Meier at 14:22, 17 May 2010

2010-05-17T14:22:49Z

@@ Line 43: / Line 43: @@
 *The main registration modules ( [[Modules:AffineRegistration-Documentation-3.6|Affine Registration]],  [[Modules:RegisterImages-Documentation-3.6|Expert Automated Registration]],  [[Modules:DeformableB-SplineRegistration-Documentation-3.6|Deformable B-Spline Registration]],  [[Modules:RegisterImagesMultiRes-Documentation-3.6|Multires Affine Registration]], [[Modules:PythonSurfaceICPRegistration-Documentation-3.6|Surface Registration]], [[  Modules:TransformFromFiducials-Documentation-3.6|Fiducial Alignment]]  etc. modules all contain a resampling option, i.e. they offer to produce a direct result volume, which includes a resampling step. In most cases the interpolation is linear. If you wish for more control over how the resampling is performed (e.g. select a different interpolator or output size or voxel size), select the registration module's option to generate an output/saved transform and then use one of the dedicated resampling modules described here to generate the new volume. The exception are modules which do '''not''' (yet) offer a transform output (e.g. Fast Nonrigid BSpline); for those you must use the module-specific resampling options to generate a result image.
 *The [[Modules:BRAINSResample|'''BRAINSresample''']] module supports applying linear transforms and deformation fields to an image, with choice of interpolation method and output datatype.
-*The [[Modules:RegisterImages-Documentation-3.6|'''Expert Automated Registration''']] module offers pure resampling from a given transform: select ''None'' for initialization and ''Initial'' for registration, specify transform under ''Load Transform'' and set the interpolation type under ''Advanced Registration Parameters''.
+*The [[Modules:RegisterImages-Documentation-3.6|'''Expert Automated Registration''']] module offers pure resampling from a given transform: select ''None'' for initialization and ''None'' for registration, specify the transform to apply under ''Load Transform'' and set the interpolation type under ''Advanced Registration Parameters''.
 = Resampling Vector- and Tensor-Data =

@@ Line 41: / Line 41: @@
 *The ''Harden Transforms'' function (context menu via the right mouse button) in the [[Modules:Data-Documentation-3.6|'''Data''' Module]] can also be used to resample an image or fiducial set through a '''linear''' transform.
 *The [[Modules:ACPCTransform-Documentation-3.6|'''AC-PC Transform''']] module lets you realign your brain image along the anterior-posterior commissure and interhemispheral midline. You (manually) select fiducials to define these points. An output transform is generated that you can then apply to the image using the resampling tools described here.
-*The main registration modules ( [[Modules:AffineRegistration-Documentation-3.6|Affine Registration]],  [[Modules:RegisterImages-Documentation-3.6|Expert Pipeline Registration]],  [[Modules:DeformableB-SplineRegistration-Documentation-3.6|Deformable B-Spline Registration]],  [[Modules:RegisterImagesMultiRes-Documentation-3.6|Multires Affine Registration]], [[Modules:PythonSurfaceICPRegistration-Documentation-3.6|Surface Registration]], [[  Modules:TransformFromFiducials-Documentation-3.6|Fiducial Alignment]]  etc. modules all contain a resampling option, i.e. they offer to produce a direct result volume, which includes a resampling step. In most cases the interpolation is linear. If you wish for more control over how the resampling is performed (e.g. select a different interpolator or output size or voxel size), select the registration module's option to generate an output/saved transform and then use one of the dedicated resampling modules described here to generate the new volume. The exception are modules which do '''not''' (yet) offer a transform output (e.g. Fast Nonrigid BSpline); for those you must use the module-specific resampling options to generate a result image.
+*The main registration modules ( [[Modules:AffineRegistration-Documentation-3.6|Affine Registration]],  [[Modules:RegisterImages-Documentation-3.6|Expert Automated Registration]],  [[Modules:DeformableB-SplineRegistration-Documentation-3.6|Deformable B-Spline Registration]],  [[Modules:RegisterImagesMultiRes-Documentation-3.6|Multires Affine Registration]], [[Modules:PythonSurfaceICPRegistration-Documentation-3.6|Surface Registration]], [[  Modules:TransformFromFiducials-Documentation-3.6|Fiducial Alignment]]  etc. modules all contain a resampling option, i.e. they offer to produce a direct result volume, which includes a resampling step. In most cases the interpolation is linear. If you wish for more control over how the resampling is performed (e.g. select a different interpolator or output size or voxel size), select the registration module's option to generate an output/saved transform and then use one of the dedicated resampling modules described here to generate the new volume. The exception are modules which do '''not''' (yet) offer a transform output (e.g. Fast Nonrigid BSpline); for those you must use the module-specific resampling options to generate a result image.
 *The [[Modules:BRAINSResample|'''BRAINSresample''']] module supports applying linear transforms and deformation fields to an image, with choice of interpolation method and output datatype.
+*The [[Modules:RegisterImages-Documentation-3.6|'''Expert Automated Registration''']] module offers pure resampling from a given transform: select ''None'' for initialization and ''Initial'' for registration, specify transform under ''Load Transform'' and set the interpolation type under ''Advanced Registration Parameters''.
 = Resampling Vector- and Tensor-Data =

@@ Line 51: / Line 51: @@
 = Resampling Surface- and Model-Data =
 *The [[Modules:ModelTransform-Documentation-3.6|'''Model Transform''']] Module reorients your surface model based on a transform. It creates a new model which is a transformed version of the input polygonal model
-*The [[Modules:Model Into Label Volume Documentation-3.6||'''Modules:Model Into Label Volume''']] module will resample a model back into a labelmap (outline, non-filled).
+*The [[Modules:Model Into Label Volume Documentation-3.6|'''Modules:Model Into Label Volume''']] module will resample a model back into a labelmap (outline, non-filled).
-*The [[Modules:PolyDataToLabelmap-Documentation-3.6||'''PolyData To Labelmap''']] module will resample a model back into a labelmap while filling the interior.
+*The [[Modules:PolyDataToLabelmap-Documentation-3.6|'''PolyData To Labelmap''']] module will resample a model back into a labelmap while filling the interior.

← Older revision		Revision as of 21:22, 17 May 2010
Line 51:		Line 51:
	= Resampling Surface- and Model-Data =		= Resampling Surface- and Model-Data =
	*The [[Modules:ModelTransform-Documentation-3.6\|'''Model Transform''']] Module reorients your surface model based on a transform. It creates a new model which is a transformed version of the input polygonal model		*The [[Modules:ModelTransform-Documentation-3.6\|'''Model Transform''']] Module reorients your surface model based on a transform. It creates a new model which is a transformed version of the input polygonal model
		+	*The [[Modules:Model Into Label Volume Documentation-3.6\|\|'''Modules:Model Into Label Volume''']] module will resample a model back into a labelmap (outline, non-filled).
		+	*The [[Modules:PolyDataToLabelmap-Documentation-3.6\|\|'''PolyData To Labelmap''']] module will resample a model back into a labelmap while filling the interior.

@@ Line 47: / Line 47: @@
 = Resampling Vector- and Tensor-Data =
 *The [[Modules:ResampleScalarVectorDWIVolume-Documentation-3.6|'''Resample ResampleScalarVectorDWIVolume''']] Module is the method of choice to realign scalar, vector or diffusion weighted data along a given transform. It supports both linear and nonlinear transforms as well as deformation fields. Note that tensor data, such as DTI has a separate volume (below).
 *The [[Modules:ResampleDTIVolume-Documentation-3.6|'''Resample DTI Volume''']] module is designed specifically for reorienting diffusion tensor MRI data.  It supports both linear and nonlinear transforms as well as deformation fields. Note that simply sending each component of a DTI tensor through the transform separately would yield an '''incorrect''' result. This module will transform the vector/tensor data correctly.
 = Resampling Surface- and Model-Data =
 *The [[Modules:ModelTransform-Documentation-3.6|'''Model Transform''']] Module reorients your surface model based on a transform. It creates a new model which is a transformed version of the input polygonal model

@@ Line 34: / Line 34: @@
 *The [[Modules:OrientImages-Documentation-3.6|'''Orient Images''']] module will sample the image data along a specified orientation scheme, such as axial/sagittal/coronal planes or RAS or LPI etc. Note that  the slices are '''not''' interpolated, they are just reordered and/or permuted. The resulting volume will cover the original volume.  Because the display is in physical space, you will not see an effect of this resampling in the viewer.
 *The [[Modules:Volumes-Documentation-3.6|'''Volumes''']] module lets you adjust the physical voxel size of an image (Info Tab), but will not generate a new volume. The changes will take effect immediately and you should see adjustments in your slice views. To obtain a new resampled volume, use the  [[Modules:ResampleVolume-Documentation-3.6|Resample Scalar Volume]] module described above.
 = Resampling via a spatial transform =
@@ Line 40: / Line 42: @@
 *The [[Modules:ACPCTransform-Documentation-3.6|'''AC-PC Transform''']] module lets you realign your brain image along the anterior-posterior commissure and interhemispheral midline. You (manually) select fiducials to define these points. An output transform is generated that you can then apply to the image using the resampling tools described here.
 *The main registration modules ( [[Modules:AffineRegistration-Documentation-3.6|Affine Registration]],  [[Modules:RegisterImages-Documentation-3.6|Expert Pipeline Registration]],  [[Modules:DeformableB-SplineRegistration-Documentation-3.6|Deformable B-Spline Registration]],  [[Modules:RegisterImagesMultiRes-Documentation-3.6|Multires Affine Registration]], [[Modules:PythonSurfaceICPRegistration-Documentation-3.6|Surface Registration]], [[  Modules:TransformFromFiducials-Documentation-3.6|Fiducial Alignment]]  etc. modules all contain a resampling option, i.e. they offer to produce a direct result volume, which includes a resampling step. In most cases the interpolation is linear. If you wish for more control over how the resampling is performed (e.g. select a different interpolator or output size or voxel size), select the registration module's option to generate an output/saved transform and then use one of the dedicated resampling modules described here to generate the new volume. The exception are modules which do '''not''' (yet) offer a transform output (e.g. Fast Nonrigid BSpline); for those you must use the module-specific resampling options to generate a result image.
 = Resampling Vector- and Tensor-Data =

@@ Line 24: / Line 24: @@
 ''Resampling decision matrix, use to find the appropriate resampling tool given your input-data and desired functionality. Note that some modules listed, although performing functions related to resampling, do '''not''' produce an output volume.
 <br>
 = Resampling in Place: Change Resolution or Field of View=
 *The [[Modules:CropVolume-Documentation-3.6|'''Crop Volume''']] module lets you clip away the image data outside an interactively defined 3D box. Such ''cropping'' is very useful to focus automated processing (e.g. registration,  segmentation) onto a region of interest or reduce memory usage and speed up performance.  The cropping includes a resampling that allows to change the resolution (''spacing'') of the result image at the same time.

← Older revision		Revision as of 14:22, 17 May 2010
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		+	*[[Slicer3:Registration\|back to Slicer Registration Portal Page]]
		+	*[[Documentation-3.6\|back to Slicer Documentation]]
		+	*[http://na-mic.org/Wiki/index.php/Projects:RegistrationDocumentation:UseCaseInventory Back To Slicer Registration Case Library]
		+
		+
	= Resampling in 3D Slicer =		= Resampling in 3D Slicer =
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