STIR Atlas Summer Work
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Transcript of STIR Atlas Summer Work
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Brain Atlas
Dan Diner
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Introduction
• PET is a nuclear imaging technique• Tracer concentrations in brain are recorded • The information collected is used for brain
study, disorder analysis, and diagnosis
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ROI/VOI Mapping
• ROIs(Regions of Interest) are small regions mapped onto brains
• Ussualy mapped out manually- very time-consuming and requires highly-paid personnel (raters)
• Raters have inter- and intra- subject variation• As PET scan quality increases, so does the
time it takes for raters to do their job
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• PET has poor spatial resolution, high temporal
• MRI has high spatial resolution• ROIs are therefore mapped onto the
MRI of a subject, onto which the PET scan is co-registered
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MRI PET Co-Registered
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Brain Atlases• An “average brain” with previously labeled
VOIs (Volumes of Interest)• labels those VOIs onto inputted images• Never have been as accurate as manual
methods, but very precise - no inter- or intra- subject variation
• much faster than manual methods
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Brain Atlases
• Many labs make their own. • Each different because each lab has own
labelling method• Could be single- or multiple-sibject• Could be made for only one specific region or
many• Probabilistic atlases tell you the probability of
a certain voxel belonging to a certain ROI
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Methods and Materials: Subject and Image Acquisition
• MRIs and PETs from 176 subjects of past studies
• 123 from a 1.5 Tesla MRI• 53 from a 3.0 Tesla
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Image Analysis Setup
• Worked on a PowerMac G5 using Mac OS X 10.5.4 Leopard
Major Software used:• Matlab (R2007a)• FSLVIEW and FLIRT• ART• iView
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Image Pre-Processing
• Raw MRI files were
copied to a common
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• Raw MRI images multiplied(matrix multiplication) by GM, WM, and CSF masks
• This got rid of all extraneous material (neck, skull, dura matter)
• Extraneous material messes with result data
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• Used iView to compare new images against raw ones
• This was done to look for undeleted extraneous material and accidentally segmented brain
• I used a scale of 0-3 to rate the new images (0= perfect, 1=some dura, 2=much dura, 3=segmented brain)
• Most images were 0s and 1s.
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Normalization Procedure
• Normalization is moving an image into a standard space
• MNI template to which were were normalizing was reoriented towards raw MRI native space
• New MRI images also normalized to this template
• We examined the normalized images, and found that some were very well aligned, but others were misplaced or improperly warped
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• warping is normalization Degrees of Freedom 9-12
• ART uses a 2-step process to warp MRIs: linear registration, then warp
• Because the rotation was bad, we thought that the linear registration had gone wrong
• We tried linear registration with FLIRT, and then warping with ART
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• The rotations came out looking good, but close inspection revealed that some leftover dura got warped into the new brain
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• An MRI with a particularly large amount of dura was manually cleaned, and then had FLIRT and ART run on it
• The resulting image was perfect
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Conclusion
• ART is very sensitive to extraneous material
• all dura needs to be properly removed from all images before normalization
• A better automatic method for cleaning up dura needs to be developed
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