Documentation/4.0/Modules/ResampleDTIVolume - Revision history

Grundlett: Text replacement - "(.)@(.)<\/email>" to "$1{{@}}$2"

2019-11-27T07:20:18Z

Text replacement - "<email>(.*)@(.*)<\/email>" to "$1{{@}}$2"

2013-06-14T07:36:30Z

Prepend documentation/versioncheck template. See http://na-mic.org/Mantis/view.php?id=2887

2012-06-19T14:56:53Z

More Information

2012-06-19T14:34:57Z

More Information

2012-06-19T14:33:47Z

More Information

2012-06-19T14:09:22Z

2012-06-19T14:08:44Z

When Using the module in command line

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 This work is part of the National Alliance for Medical Image Computing (NA-MIC), funded by the National Institutes of Health through the NIH Roadmap for Medical Research, Grant U54 EB005149. Information on NA-MIC can be obtained from the [http://www.na-mic.org/ NA-MIC website].<br>
 Author: Francois Budin, NIRAL, University of North Carolina; Demian Wassermann, SPL, LMI, PNL, Brigham and Women's Hospital, Harvard Medical School<br>
-Contact:  Demian Wassermann, <email>demian@bwh.harvard.edu</email><br>
+Contact:  Demian Wassermann, demian{{@}}bwh.harvard.edu<br>
 Contributor1: Sylvain Bouix<br>
 Contributor2: Raúl San José-Estepar<br>

← Older revision		Revision as of 07:36, 14 June 2013
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 * Resample Scalar/Vector/DWI Volume is the equivalent module for DWI, scalar and vector images
-== More Information ==
+= More Information =
 * The transform can be passed as an ITK Transform file using the command line, or directly as a transform node in Slicer. In the latter case, the transform can only be rigid or affine.
 * '''Be careful''' when applying multiple transforms contained in one file. Pay attention to the order of the transforms in the file and if those transforms are applied serially or simultaneously (bulk).
 * '''Warning :''' When using this module in Microsoft Windows, the flag -c which centers the transform might cause problems. Please use the long flag --centered_transform instead in that case.
 * The Transform can be given through an ITK Transform file. An example is given below.

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 * The transform can be passed as an ITK Transform file using the command line, or directly as a transform node in Slicer. In the latter case, the transform can only be rigid or affine.
 * '''Be careful''' when applying multiple transforms contained in one file. Pay attention to the order of the transforms in the file and if those transforms are applied serially or simultaneously (bulk).
 * '''Warning :''' When using this module in Microsoft Windows, the flag -c which centers the transform might cause problems. Please use the long flag --centered_transform instead in that case.
 * The Transform can be given through an ITK Transform file. An example is given below.

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 * The transform can be passed as an ITK Transform file using the command line, or directly as a transform node in Slicer. In the latter case, the transform can only be rigid or affine.
-* '''Be careful''' when applying multiple transforms contained in one file. Pay attention to the order of the transforms in the file. You may also not obtain the same result as other tools would give you. For example, if you register two images using BRAINSFit using an affine and a BSpline transform simultaneously, the output file will contain two transforms. However these two transforms are actually two components of the same transform and should be applied simultaneously. Resample DTI Volume only applies transforms serially. You should therefore not use Resample DTI Volume in this case.
+* '''Be careful''' when applying multiple transforms contained in one file. Pay attention to the order of the transforms in the file and if those transforms are applied serially or simultaneously (bulk).
 * '''Warning :''' When using this module in Microsoft Windows, the flag -c which centers the transform might cause problems. Please use the long flag --centered_transform instead in that case.
 * The Transform can be given through an ITK Transform file. An example is given below.

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 * '''Advanced Transform Parameters'''
 ** '''Not a Bulk Transform''': The transform following the BSpline transform is not set as a bulk transform for the BSpline transform
-** '''Space Orientation inconsistency (between transform and image)''': Space Orientation between transform and image is different (RAS/LPS) (warning: if the transform is a Transform Node in Slicer3, do not select)
+** '''Space Orientation inconsistency (between transform and image)''': Space Orientation between transform and image is different (RAS/LPS) (warning: if the transform is a Transform Node in Slicer, do not select)
 ** '''Transforms Order''': Select the order in which the transforms are read in the transform node (or file).

← Older revision		Revision as of 14:07, 19 June 2012
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	* It also allows changing the spacing, the orientation, the size and the origin of the image. In that case, the image will be modified in consequences.		* It also allows changing the spacing, the orientation, the size and the origin of the image. In that case, the image will be modified in consequences.

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−	~~{{documentation/{{documentation/version}}/module-section\|Tutorials}}~~
−	~~Links to tutorials that use this module~~

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 ** '''Input volume''': input volume to be resampled
 ** '''Output volume''': Resampled Volume
-** '''Reference Volume''' (optional) is the volume used to set the sampling parameters (origin, spacing, orientation and dimensions). If it is not set, the input volume will be taken for reference.
+** '''Reference Volume''' (optional): Volume used to set the sampling parameters (origin, spacing, orientation and dimensions). If it is not set, the input volume will be taken for reference.
 * '''Transform Parameters'''
 ** '''Transform Node''' contains the transform(s) to apply to the image

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 {{documentation/{{documentation/version}}/module-section|Information for Developers}}
-{{documentation/{{documentation/version}}/module-developerinfo}}
-Developpers can use the C++ classes available in this module to resample Diffusion Tensor Images. The classes are based on ITK.
+Developers can use the C++ classes available in this module to resample Diffusion Tensor Images. The classes are based on ITK.
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