Projects:DBP2:Harvard:Registration Documentation - Revision history

Rauscha at 19:15, 19 May 2009

2009-05-19T19:15:20Z

2009-05-19T15:59:02Z

2009-05-19T15:49:21Z

2009-05-18T14:31:42Z

Archana's transform

2009-05-18T14:31:28Z

Archana's transform

2009-05-18T14:31:07Z

Archana's transform

2009-05-18T14:30:45Z

Freesurfer parcellation overlay

2009-05-15T15:38:42Z

2009-05-15T15:15:39Z

Freesurfer parcellation overlay

2009-05-15T15:15:13Z

Freesurfer parcellation overlay

← Older revision		Revision as of 19:15, 19 May 2009
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	Talk to Andrew Rausch, rauscha@bwh.harvard.edu for more info. I'm no expert on registration, but I can tell you exactly how each of these were performed and provide mrmls and nrrds.		Talk to Andrew Rausch, rauscha@bwh.harvard.edu for more info. I'm no expert on registration, but I can tell you exactly how each of these were performed and provide mrmls and nrrds.
		+
		+	A concise comparison of FSL and slicer registrations can be found [[Projects:DBP2:Harvard:Registration_Documentation:Compare\|here]].

	'''The data set used for testing can be downloaded [http://pnl.bwh.harvard.edu/people/sylvain/registration_files.tar.gz here].'''		'''The data set used for testing can be downloaded [http://pnl.bwh.harvard.edu/people/sylvain/registration_files.tar.gz here].'''

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 '''The data set used for testing can be downloaded [http://pnl.bwh.harvard.edu/people/sylvain/registration_files.tar.gz here].'''
 =There and back registration=
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 [[File:53-31 RI pipe bspline.png|600px|thumb|left|Pipe B-Spline: good registration, but quite blurred. (source on left, target on right, registered image in middle.)]]
 >01031_RI_pipe_bspline.png - good coregistration, but pretty blurred. also, I would have expected the temporal lobe to be coregistered better.

← Older revision		Revision as of 15:49, 19 May 2009
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	Talk to Andrew Rausch, rauscha@bwh.harvard.edu for more info. I'm no expert on registration, but I can tell you exactly how each of these were performed and provide mrmls and nrrds.		Talk to Andrew Rausch, rauscha@bwh.harvard.edu for more info. I'm no expert on registration, but I can tell you exactly how each of these were performed and provide mrmls and nrrds.
		+
		+	'''The data set used for testing can be downloaded [http://pnl.bwh.harvard.edu/people/sylvain/registration_files.tar.gz here].'''

	=Special case: Anna's data registration=		=Special case: Anna's data registration=

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 [[File:Archana aseg baseline.png|600px|thumb|right|Archana's affine registration: some problems in the back of the brain, but reasonable registration in front.  Still some mismatch with DTI distortion.]]
 Archana is an MIT grad student working on fMRI -> DTI registration.  She used an affine transformation of some sort (I'm pretty sure it wasn't Slicer) to register a masked T2 to the masked DTI baseline, and transformed the freesurfer aseg the same way.  You can see her registration has the same problems in the back of the brain, going beyond the borders of our image, but there is better registration in the front, matching up to the DTI distortion.
-<br><br><br><br><br><br><br><br><br><br><br><br><br>
+<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>
 ==Slicer modules==

@@ Line 147: / Line 147: @@
 [[File:Archana aseg baseline.png|600px|thumb|right|Archana's affine registration: some problems in the back of the brain, but reasonable registration in front.  Still some mismatch with DTI distortion.]]
 Archana is an MIT grad student working on fMRI -> DTI registration.  She used an affine transformation of some sort (I'm pretty sure it wasn't Slicer) to register a masked T2 to the masked DTI baseline, and transformed the freesurfer aseg the same way.  You can see her registration has the same problems in the back of the brain, going beyond the borders of our image, but there is better registration in the front, matching up to the DTI distortion.
-<br><br><br><br><br><br><br><br>
+<br><br><br><br><br><br><br><br><br><br><br><br><br>
 ==Slicer modules==

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 [[File:Aparc-overlay-affine.png|600px|thumb|left|Affine aparc overlay: few matches, linear method doesn't allow for good fit.]]
-The overlay has very few places where it is even usable, only in the dead center of ROIs do you have any guarantee of being in the same region on the DTI. This is only a linear registration, so the label map cannot account for the DTI distortion.
+The overlay has only a few places where it is usable, only in the center of ROIs you'll probably be in the same region on the DTI.
 ===Linear===
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 The overlay is useful in roughly the middle third of the brain, distortion of DTI means linear transform cannot match in the front or back of brain.
 ==Slicer modules==

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 * Registering a DTI baseline image to the corresponding realigned t2 weighted image, and vice-versa.  This is a realistic test of one of our (the PNL) everyday uses of registration.
 * Registering a realigned t2 weighted image to another t2.
 Talk to Andrew Rausch, rauscha@bwh.harvard.edu for more info.  I'm no expert on registration, but I can tell you exactly how each of these were performed and provide mrmls and nrrds.

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 Only linear methods produce transforms that can be used to register a label map.  Unfortunately, a linear registration can never account for the distortions of a DTI image, and as such there is no way to get a good registration of structural label maps to DTI space.  In Slicer 2, I can create a transform node and do an automatic registration between two already created nrrds based on intensity via diff. demons or bspline, and then apply that transform to a label map, but I don't know of any way to get a similar transform in Slicer3.
-*Note: actually need to apply a transform volume, not a transform node to make this work in slicer 2.  Still don't know how to accomplish this (or get a transform node) in Slicer 3.
+<nowiki>*</nowiki>Note: actually need to apply a transform volume, not a transform node to make this work in slicer 2.  Still don't know how to accomplish this (or get a transform node) in Slicer 3.
 ===Affine===

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 ==Freesurfer parcellation overlay==
-Only linear methods produce transforms that can be used to register a label map.  Unfortunately, a linear registration can never account for the distortions of a DTI image, and as such there is no way to get a good registration of structural label maps to DTI space.  In Slicer 2, I can create a transform node and do an automatic registration between two already created nrrds based on intensity via diff. demons or bspline, and then apply that transform to a label map, but I don't know of any way to get a similar transform in Slicer3. *Note: actually need to apply a transform volume, not a transform node to make this work in slicer 2.  Still don't know how to accomplish this (or get a transform node) in Slicer 3.
+Only linear methods produce transforms that can be used to register a label map.  Unfortunately, a linear registration can never account for the distortions of a DTI image, and as such there is no way to get a good registration of structural label maps to DTI space.  In Slicer 2, I can create a transform node and do an automatic registration between two already created nrrds based on intensity via diff. demons or bspline, and then apply that transform to a label map, but I don't know of any way to get a similar transform in Slicer3.
 ===Affine===