View source for DBP3:Utah:RegSegPipeline

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= The CARMA DBP: MRI-based study and treatment of atrial fibrillation =
Alex Zaitsev, Dominik Meier, Ron Kikinis

== Pilot Studies on a Registration & Segmentation Pipeline & Workflow ==
=== Main processing pipeline ===
#N4 bias field correction for the MRI (surface coils): 
## run  on entire image gives some benefit that '''may''' be improved with masking: again the dominant intensity dropoff from the surface coil occurs along the chest wall and ribcage. Even if that is not the structure of interest, it is the low-freq. variation the bias correction algorithm is searching for, and masking that out can be counter-productive: via masking we may end up with a smoother image, but the intensity variations removed were not caused by the coil but are actually true signal.
##Module used: [http://www.slicer.org/slicerWiki/index.php/Modules:N4ITKBiasFieldCorrection-Documentation-3.6 N4 ITK]; '''Parameters:''' convergence: 1e-5, iterations: 50,40,30,20, shrink factor: 3 
#registration MRA>cMRI
##the MRA contains the same FOV and has surrounding structures (liver, chest, spine etc) visible also, despite lower intensities. A global affine is thus not necessarily going to benefit from masking the heart, unless the relative motion of the heart becomes the dominant reason for misalignment.
##Module used: [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
###tried masking with both BrainsFit and RobustMultires modules. Both failed to provide better alignment with masking.
###images have good alignment to begin with, need reliable fiducial to evaluate registration. E..g. descending aorta? non-cardiac structures?
#registration follow-up -> baseline
##most reliably done on the post contrast MRI.
##DOF at least 12, because image is captured at different phases in the breathing/cardiac cycle, some low-res BSpline should be beneficial
##Module used: [http://www.slicer.org/slicerWiki/index.php/Modules:BRAINSFit BRAINSfit]
##the IS FOV can differ, e.g. how much of the liver is included. If the two exams differ significantly (>30%) in that content, a prior cropping step is suggested to better match image content before registration. Resampling to isotropic voxel size at this stage is also advantageous.
#ROI definition (manual box ROI or automated via atlas)
#segmentation of LA from MRA -> inner wall
##as a dynamic image the MRA contains significant spread and likely requires interactive segmentation/thresholding to yield a satisfactory LA volume
##Module used: [http://www.slicer.org/slicerWiki/index.php/Modules:Editor-Documentation-3.6 Editor: thresholding]  or thresholding within [http://www.slicer.org/slicerWiki/index.php/Modules:Volumes-Documentation-3.6 Volumes thresholding option within ''Display'' tab, use ''iron'' colormap & low alpha setting to check for ventricular wall borders.]  

##cropping and island removal
#LA wall segmentation
## very small structure, most reliably done manually direct. Starting with automation may yield more effort on post-edits
##Module used: [http://www.slicer.org/slicerWiki/index.php/Modules:Editor-Documentation-3.6 Editor: manual outline]  
#segmentation of enhancement within LA wall: intensity statistics. An atlas-based set of intensity distributions may be more meaningful here than a simple Otsu, because both amount and location of enhancement is unknown and can in theory be 0. 

<gallery perrow="4" widths="200px">
Image:DBP3_AFib_LV_overlay_1.jpg| Example contrast MRI with thresholded MRA as color overlay.  Registration validation is not trivial: we can in theory use the position of the blood in the MRA relative to the LV wall as registration check, but the MRA itself does not provide a clear boundary at the lower intensities. 
Image:DBP3_AFib_LA_overlay_2.jpg|Example contrast MRI with thresholded MRA as color overlay and areas of enhancement marked
Image:DBP3_histogramMRA.png|Histogram of MRA intensities: green = entire FOV, red: cardiac structures only (excl. aorta), which make only 6% of the total image content and thus are unlikely to disturb a registration based on the entire image. 
Image:DBP3_Biasfield_masked-unmasked.png|Bias field correction results (N4ITK) with and without masking of the structures of interest. Masking causes a different correction not related to coil sensitivity but rather local image content. Masking is not recommended at this point. 

</gallery>

=== Example Cases ===
* [[Media:AFib_Example_P2_Data.zip|Example Case P2 : pre-post registration]]
**This example contains significant MRI (motion?) artifacts that require dedicated processing to isolate the structures of interest
**E.g. FOV includes much more of liver on pre exam, which needs to be cropped to amount matching the follow-up