Difference between revisions of "Registration:Resampling"

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Resampling builds a new dataset (image, surface, fiducials etc.) from an existing one, but with a different orientation, resolution, field of view or aspect ratio. For example the last step in registering two images consists of two main steps: finding the transform and resampling according to this transform. So the last step in registration will be to resample the moving data according to a spatial transform function, and thereby generate a new and aligned image. Or changing the voxel size to something larger or smaller involves resampling.  
 
Resampling builds a new dataset (image, surface, fiducials etc.) from an existing one, but with a different orientation, resolution, field of view or aspect ratio. For example the last step in registering two images consists of two main steps: finding the transform and resampling according to this transform. So the last step in registration will be to resample the moving data according to a spatial transform function, and thereby generate a new and aligned image. Or changing the voxel size to something larger or smaller involves resampling.  
 
[http://en.wikipedia.org/wiki/Resampling  See Wikipedia for a more detailed definition].
 
[http://en.wikipedia.org/wiki/Resampling  See Wikipedia for a more detailed definition].
 +
'''Interpolation''' is the process of estimating the value of the data based on surrounding values. This is necessary because spatial realignment is unlikely to be in exact multiples of voxel sizes.  Please pay attention to selecting the proper interpolation method for your data-type: For more detail on ''interpolation'' we recommend this [http://en.wikipedia.org/wiki/Interpolation Wikipedia article].
  
 
= Resampling in Place: Change Resolution or Field of View=
 
= Resampling in Place: Change Resolution or Field of View=
 
*The crop volume module...
 
*The crop volume module...
*The [[Modules:ResampleVolume-Documentation-3.6|'''Resample Scalar Volume''']] Module changes resolution (''spacing'') of an image. Several interpolation options.
+
*The [[Modules:ResampleVolume-Documentation-3.6|'''Resample Scalar Volume''']] Module changes resolution (''spacing'') of an image. This is the method of choice if you wish to increase or decrease the number of voxels per mm or make the voxel size isotropic. It contains several interpolation options for different data types.  
  
 
= Resampling via a spatial transform =
 
= Resampling via a spatial transform =
 
*The [[Modules:ResampleScalarVectorDWIVolume-Documentation-3.6|'''Resample ResampleScalarVectorDWIVolume''']] Module sends both scalar and vector images through a transform. Several interpolation options.
 
*The [[Modules:ResampleScalarVectorDWIVolume-Documentation-3.6|'''Resample ResampleScalarVectorDWIVolume''']] Module sends both scalar and vector images through a transform. Several interpolation options.
*The ''Harden Transforms'' function in the Data Module
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*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.
 
= Resampling Vector- and Tensor-Data =
 
= Resampling Vector- and Tensor-Data =
 +
*The [[Modules:ResampleScalarVectorDWIVolume-Documentation-3.6|'''Resample ResampleScalarVectorDWIVolume''']] Module is the method of choice to realign vector or tensor data, such as DTI along a given transform. Note that simply sending each component of the vector or tensor through the transform separately would yield an '''incorrect''' result. This module will transform the vector/tensor data correctly.
  
 
= 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.
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*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
  
  
 
= Related Functions =
 
= Related Functions =

Revision as of 14:42, 3 May 2010

Home < Registration:Resampling

Resampling in 3D Slicer

Several distinct tools are available within 3D Slicer for resampling image data to change orientation, resolution or field of view. The organization below is intended to help you choose the best module for your task

Note that there are also many related functions that change aspects of the image without requiring a resampling, e.g. changing the aspect ratio or slice view orientation. They are listed in a separate category below.
If you find something amiss, please let us know so we can amend (meier at bwh.harvard.edu).

Slicer Registration Case Library: Call for Example Datasets

Consider adding your case to the library: If your resampling task is related to a registration problem, we can (for 2010-2011) offer you direct consulting: If we can add your (anonymized) case to the Library, we will assist you with registering/resampling by processing your case and providing step-by-step instructions and best-practice tips. See here for details.

What we mean by Resampling

Resampling builds a new dataset (image, surface, fiducials etc.) from an existing one, but with a different orientation, resolution, field of view or aspect ratio. For example the last step in registering two images consists of two main steps: finding the transform and resampling according to this transform. So the last step in registration will be to resample the moving data according to a spatial transform function, and thereby generate a new and aligned image. Or changing the voxel size to something larger or smaller involves resampling. See Wikipedia for a more detailed definition. Interpolation is the process of estimating the value of the data based on surrounding values. This is necessary because spatial realignment is unlikely to be in exact multiples of voxel sizes. Please pay attention to selecting the proper interpolation method for your data-type: For more detail on interpolation we recommend this Wikipedia article.

Resampling in Place: Change Resolution or Field of View

  • The crop volume module...
  • The Resample Scalar Volume Module changes resolution (spacing) of an image. This is the method of choice if you wish to increase or decrease the number of voxels per mm or make the voxel size isotropic. It contains several interpolation options for different data types.

Resampling via a spatial transform

  • The Resample ResampleScalarVectorDWIVolume Module sends both scalar and vector images through a transform. Several interpolation options.
  • The Harden Transforms function (context menu via the right mouse button) in the Data Module can also be used to resample an image or fiducial set through a linear transform.

Resampling Vector- and Tensor-Data

  • The Resample ResampleScalarVectorDWIVolume Module is the method of choice to realign vector or tensor data, such as DTI along a given transform. Note that simply sending each component of the vector or 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 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


Related Functions