View source for Initial atlas construction workflow

== Content ==

This page describes the current working pipeline of atlas construction for vervet data.

== Data ==

10 vervet subjects (2 subjects possibly have unacceptable image quality), T1 sequence

== Workflow / Tools ==

{| class="wikitable" style="text-align:center; width:800px; height:200px" border="1"
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! Workflow step !! Description !! Tools 
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! 1. Preparation
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1.1. Select the subject that is best oriented as the template image 

1.2. Manually identify the ICC in the template subject.

1.3. Perform intensity calibration for all other subjects to the template.

1.4. 12 DOF registration of each of the subjects to the template.

1.5. Skull-strip each subject using dilated ICC of the template.

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1.1. n/a

1.2. manual in SNAP.

1.3. Slicer Histogram Matching module

1.4. FSL-Flirt

1.5. Slicer Mask, Editor modules (verify the mask encloses actual ICC!)

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! 2. Atlas construction
| 

2.1. Use the skullstriped image from Step 1.2 as the template to repeat Step 1.4.

2.2. Perform non-rigid alignment of the subjects affinely registered to the template.

2.3. Compute the atlas as the average.

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2.1 see above 

2.2. Diffeomorphic demons

2.3. Some tool in Slicer under development

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! 3. Probabilistic atlas construction
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3.1. Segment WM/GM/CSF from the averaged template, manually edit to ensure accuracy

3.2. Slightly smooth the segmentations Styner et al. recommend kernel of 0.4 mm variance.

3.3. Probabilistic atlas is the result of smoothing of the hard segmentation of the averaged template with Gaussian kernel.

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3.1. Kmeans + manual

3.2. Gaussian smoothing module in Slicer, 0.6 and 0.65 kernel size used for Valentino and Tommy, respectively. '''AF: I do not understand what is the relation of Valentino and Tommy to this, if the operation was performed on hard segmentation from the average template'''

3.3. Slicer Gaussian smoothing module

*We did not perform back propagation as in Styner07 due to the large structural differences in the dataset.

|}

== References ==

# M. Styner, R. Knickmeyer, S. Joshi, C. Coe, S. J. Short, and J. Gilmore. Automatic brain segmentation in rhesus monkeys. Proc SPIE Medical Imaging Conference, Proc SPIE Vol 6512 Medical Imaging 2007, pp 65122L-1 - 65122L-8 [http://www.google.com/url?sa=t&source=web&ct=res&cd=1&url=http%3A%2F%2Fwww.cs.unc.edu%2F~styner%2Fpublic%2FMyPapers%2Fpapers%2FMedical%2520Imaging%25202007%2520Image%2520Processing%25202007%2520Styner-1.pdf&ei=DubDSt3AAciwlAfJp5TwBA&usg=AFQjCNGojUvBkh6TwbS0vJ9X7OEFLDFxqQ&sig2=wHgXTrdAXzUC5DuL_C7CCQ pdf]
# Balci S.K., Golland P., Wells W.M. Non-rigid Groupwise Registration using B-Spline Deformation Model. Insight Journal - 2007 MICCAI Open Science Workshop. [http://hdl.handle.net/1926/568 link]
# Previous descriptions of the atlas construction workflow: [http://wiki.na-mic.org/Wiki/index.php/Atlas-to-subject_registration_with_FSL_and_Diffeomorphic_Demons,_for_EM_segmentation. Summary by Ginger Li], [http://www.bsl.ece.vt.edu/data/vervet_atlas/vervet.php Description off BSL atlas page]