Documentation:Nightly:Registration:RegistrationLibrary:RegLib C04 - Revision history

Meier: /* Download (from NAMIC MIDAS) */

2013-08-30T22:07:05Z

Download (from NAMIC MIDAS)

Meier: /* Description */

2013-08-30T22:00:06Z

Description

Meier: /* Description */

2013-08-30T21:59:55Z

Description

Meier: /* Description */

2013-08-30T21:59:45Z

Description

Meier: /* Registration Results */

2013-08-30T21:58:47Z

Registration Results

Meier: /* Procedure */

2013-08-30T21:55:55Z

Procedure

Meier: /* Procedure */

2013-08-30T21:55:38Z

Procedure

Meier: /* Description */

2013-08-30T21:55:08Z

Description

Meier: /* Procedure */

2013-08-30T21:54:37Z

Procedure

Meier: /* Description */

2013-08-30T21:42:49Z

Description

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 == Download (from NAMIC MIDAS) ==
 <small>''Why 2 sets of files?  The "input data" mrb includes only the unregistered data to try the method yourself from start to finish. The full dataset includes intermediate files and results (transforms, resampled images etc.). If you use the full dataset we recommend to choose different names for the images/results you create yourself to distinguish the old data from the new one you generated yourself. ''</small>
-*[http://slicer.kitware.com/midas3/download/?items=xx '''RegLib_C04.mrb''': input data only, use this to run the tutorial from the start <small>(Slicer mrb file. 19 MB). </small>]
+*[http://slicer.kitware.com/midas3/download/?items=116480 '''RegLib_C04.mrb''': input data only, use this to run the tutorial from the start <small>(Slicer mrb file. 19 MB). </small>]
-*[http://slicer.kitware.com/midas3/download/?items=xx '''RegLib_C04_full.mrb''': includes raw data + all solutions and intermediate files, use to browse/verify <small>(Slicer mrb file. 19 MB). </small>]
+*[http://slicer.kitware.com/midas3/download/?items=116479 '''RegLib_C04_full.mrb''': includes raw data + all solutions and intermediate files, use to browse/verify <small>(Slicer mrb file. 19 MB). </small>]
 == Keywords ==

@@ Line 30: / Line 30: @@
 ==Description ==
-This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice). You can read
+This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice). You can find
 [http://na-mic.org/Wiki/index.php/Projects:RegistrationLibrary:RegLib_C04:read more about this dataset here.]
 <br>

@@ Line 30: / Line 30: @@
 ==Description ==
-This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice). You can
+This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice). You can read
 [http://na-mic.org/Wiki/index.php/Projects:RegistrationLibrary:RegLib_C04:read more about this dataset here.]
 <br>

@@ Line 30: / Line 30: @@
 ==Description ==
-This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice).
+This scenario occurs in many forms whenever we wish to assess change in a series of multi-contrast MRI. The follow-up scan(s) are to be aligned with the baseline, but also the different series within each exam need to be co-registered, since the subject may have moved between acquisitions. Hence we have a set of nested registrations. This particular exam features a dual echo scan (PD/T2), where the two structural scans are aligned by default. The post-contrast T1-GdDTPA scan however is not necessarily aligned with the dual echo. Also the post-contrast scan is taken with a clipped field of view (FOV) and a lower axial resolution, with 4mm slices and a 1mm gap (which we treat here as a de facto 5mm slice). You can
-[http://na-mic.org/Wiki/index.php/Projects:RegistrationLibrary:RegLib_C04:About read more about this dataset here]
+[http://na-mic.org/Wiki/index.php/Projects:RegistrationLibrary:RegLib_C04:read more about this dataset here.]
 <br>
 '''Approach''': we first compute the 2 intra-exam registrations aligning the T1Gd contrast exam with the PD of the same exam. We then register the PDs of the two exams to eachother. This provides a complete hierarchy that aligns everything to the baseline. Placing the  follow-up/"exam 2" T2 and (T1Gd incl. transform) inside the inter-exam transform will bring all scans into alignment.

@@ Line 108: / Line 108: @@
 {|cellpadding="10" cellspacing="0" border="0"
-|[[Image:RegLib_C02_unregistered.gif|300px]] ||baseline & T2 before registration (click to enlarge)
+|[[Image:RegLib_C04_unregistered1.gif|300px]] ||baseline PD & contrast T1Gd before registration (click to enlarge)
 |-
-|[[Image:RegLib_C02_registered.gif|300px]]||baseline to T2 after affine+nonrigid alignment (click to enlarge)
+|[[Image:RegLib_C04_unregistered2.gif|300px]]||baseline and follow-up PD before registration (click to enlarge)
 |}
 === Acknowledgments ===

@@ Line 85: / Line 85: @@
 ##drag the transform node Xf3_e2_T1Gd_Rigid.tfm onto the transform Xf1_e21_Affine.tfm
 ##drag the entire transform  Xf2_e2-T1Gd_Affine '''and its contents''' onto the transform Xf3_e21_Affine.tfm
-##your MRML data tree should look like this: [[Image:RegLib_C04_TransformHierarchy.png|100px|lleft|transform hierarchy of inter- and intra-exam registration, bringing everything into alignment with the baseline PD/T2 pair. ]]
+##your MRML data tree should look something like this: [[Image:RegLib_C04_TransformHierarchy.png|100px|lleft|transform hierarchy of inter- and intra-exam registration, bringing everything into alignment with the baseline PD/T2 pair. ]]
 #'''Apply Transform (without resampling''')

@@ Line 33: / Line 33: @@
 [http://na-mic.org/Wiki/index.php/Projects:RegistrationLibrary:RegLib_C04:About read more about this dataset here]
 <br>
-'''Approach''': we first compute the 2 intra-exam registrations aligning the T1Gd contrast exam with the PD of the same exam. We then register the PDs of the two exams to eachother. This provides a complete hierarchy that aligns everything to the baseline. Placing the  follow-up/"exam 2" T2 and (T1Gd incl. transform) inside the inter-exam transform will bring all scans into alignment. We will have a hierarchy that looks like this:
+'''Approach''': we first compute the 2 intra-exam registrations aligning the T1Gd contrast exam with the PD of the same exam. We then register the PDs of the two exams to eachother. This provides a complete hierarchy that aligns everything to the baseline. Placing the  follow-up/"exam 2" T2 and (T1Gd incl. transform) inside the inter-exam transform will bring all scans into alignment.
 == Modules used ==

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 == Procedure ==
-#'''Compute Registration''': open the [[Documentation/Nightly/Modules/BRAINSFit|''General Registration (BRAINS)'' module]]
+#'''Intra-Exam''': register intra-examT1Gd to PD
-##''Input Images: Fixed Image Volume'': T1
+##open the [[Documentation/Nightly/Modules/BRAINSFit|''General Registration (BRAINS)'' module]]
-##''Input Images: Moving Image Volume'': FLAIR
+##''Fixed Image Volume'': e1_PD
-##''Output Settings'':
+##''Moving Image Volume'': e1_T1Gd
-###''Slicer Linear Transform'' (create new transform, rename to: "Xf1_Affine")
+##Output Settings:
-###''Output Image Volume'' none. No resampling required for linear transforms
+###''Slicer BSpline Transform": none
-##''Registration Phases'':  select/check ''Rigid'' , ''Rigid+Scale'', ''Affine''
+###''Slicer Linear Transform'': create & rename new transform: Xf1_e1-T1Gd_Affine.tfm
-##''Main Parameters'':
+###''Output Image Volume'': none
-###increase ''Number Of Samples'' to 200,000
+##''Registration Phases'': check boxes for ''Rigid'', ''Rigid+Scale'' and ''Affine''
-##Leave all other settings at default
+##''Main Parameters''
-##click: ''Apply''; runtime < 1 min.
+###'''Number of Samples''': 200,000
-#'''Align Labelmap:''' We have now computed the registration transform. To reorient both FLAIR and its label map, we place both volumes inside the transform.
+##click: Apply; runtime < 10 sec (MacPro QuadCore 2.4GHz)
-###Place "T1" in the background and "FLAIR" in the foreground. Select "LesionSeg" as the labelmap to display.
+#'''repeat for exam 2''', i.e
-##Go to the [[Documentation/Nightly/Modules/Data|''Data'']] module
+##''Fixed Image Volume'': e2_PD
-###the "FLAIR" image should already be placed within the transform "Xf1_Affine", that was done by the registration module. If not, left click on the "FLAIR" node and drag it onto the "Xf1_Affine" node. You will see a "+" sign appear indicating that the image is placed within the transform.
+##''Moving Image Volume'': e2_T1Gd
-###Do the same for the "LesionSeg" node, i.e. drag it into the "Xf1_Affine" transform.
+##''Slicer Linear Transform'': create & rename new transform: Xf2_e2-T1Gd_Affine.tfm
-#'''Apply the transforms without resampling / Save result images'''
+#'''Inter-Exam Registration''': register exam 2 -> exam 1
 ##for linear (rigid to affine) transforms you have two options for generating a result image in the new orientation: with and without resampling. The method without resampling leaves the original image data untouched and writes the new orientation into the image header. This preserves the full original image quality and is the preferred method, provided that the software using the result image can read the spatial information in the header correctly. If you open an image with a software that does not account for this header information, the image will appear in its original orientation. The resampling method will create a new image volume by interpolating the data into the new space. This has the advantage that your registered volume will have matching size and resolution as your reference image, but it is associated with some data loss from the interpolation during resampling.
 ##''Apply Transform without resampling'':
@@ Line 76: / Line 96: @@
 #Alternative: '''Apply Transform with resampling''':
 ##Go to the [[Documentation/Nightly/Modules/BRAINSResample|''BRAINSResample'' module]]
-###''Image To Warp'': select FLAIR
+###''Image To Warp'': select e2_PD
-###''Reference Image'': select T1
+###''Reference Image'': select e1_PD
-###''Outputs:OutputImage'': create & rename new, rename to "FLAIR_Xf1"
+###''Outputs:OutputImage'': create & rename new, rename to "e2_PD_Xf3"
 ###''Pixel Type'': select ''short'' , or match the datatype of the original image.
-###''Transform File'': select "Xf1_Affine"
+###''Transform File'': select "Xf3_e21_Affine.tfm"
 ###''Interpolation Mode'': select "WindowedSinc" (recommended for 3D MRI). For labelmaps select ''Nearest Neighbor''
 ###Click Apply. This will generate a new volume with the same resolution as the reference image.