EMSegmenter-Tasks:MRI-Human-Brain-Parcellation

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Description

MRI Human Head pipeline for a finer-grained parcellation (TODO: Priya please provide description and proper citation)

The pipeline consist of the following steps:

• Step 1: Perform image inhomogeneity correction of the MRI scan via N4ITKBiasFieldCorrection (Tustison et al 2010)
• Step 2: Register the atlas to the MRI scan via BRAINSFit (Johnson et al 2007)
• Step 3: Compute the intensity distributions for each structure
  

Compute intensity distribution (mean and variance) for each label by automatically sampling from the MR scan. The sampling for a specific label is constrained to the region that consists of voxels with high probability (top 95%) of being assigned to the label according to the aligned atlas.

• Step 4: Automatically segment the MRI scan into the structures of interest using EM Algorithm (Pohl et al 2007)

Anatomical Tree

The anatomical tree represents the structures to be segmented. Node labels displayed below contain a human readable structure name and in parentheses the internally used structure name.

• Root
  • background (BG)
  • grey matter (GM)
    • left grey matter (LTGM)
      • left grey matter - region 1 (LTGM1)
      • left grey matter - region 2 (LTGM2)
      • left grey matter - region 3 (LTGM3)
      • left grey matter - region 4 (LTGM4)
    • right grey matter (RTGM)
      • right grey matter - region 1 (RTGM1)
      • right grey matter - region 2 (RTGM2)
      • right grey matter - region 3 (RTGM3)
      • right grey matter - region 4 (RTGM4)
    • subcortical grey matter (SUBGM)
  • white matter (WM)
    • left white matter (LTWM)
      • left white matter - region 1 (LTWM1)
      • left white matter - region 2 (LTWM2)
      • left white matter - region 3 (LTWM3)
      • left white matter - region 4 (LTWM4)
    • right white matter (RTWM)
      • right white matter - region 1 (RTWM1)
      • right white matter - region 2 (RTWM2)
      • right white matter - region 3 (RTWM3)
      • right white matter - region 4 (RTWM4)
    • subcortical white matter (SUBWM)
  • cerebrospinal fluid (CSF)

Atlas

The atlas has been created by Padmapriya Srinivasan and Ryan Eckbo and Sylvain Bouix from (PNL-BWH)

Image Dimension = 256 x 256 x 220
Image Spacing = 0.9375 x 0.9375 x 0.9375

TODO, some details about the combined atlas

Template (T1)	CSF	Left Temporal GM	Left Temporal WM

Result

Collaborators

Padmapriya Srinivasan and Sylvain Bouix (PNL-BWH)

Acknowledgment

The construction of the pipeline was supported by funding from NIH NCRR 2P41RR013218 Supplement.

Citations

• Tustison NJ, Avants BB, Cook PA, Zheng Y, Egan A, Yushkevich PA, Gee JC N4ITK: Improved N3 Bias Correction, IEEE Trans Med Imag, 2010
• Pohl K, Bouix S, Nakamura M, Rohlfing T, McCarley R, Kikinis R, Grimson W, Shenton M, Wells W. A Hierarchical Algorithm for MR Brain Image Parcellation. IEEE Transactions on Medical Imaging. 2007 Sept;26(9):1201-1212.
• S. Warfield, J. Rexilius, P. Huppi, T. Inder, E. Miller, W. Wells, G. Zientara, F. Jolesz, and R. Kikinis, “A binary entropy measure to assess nonrigid registration algorithms,” in MICCAI, LNCS, pp. 266–274, Springer, October 2001.
• Johnson H.J., Harris G., Williams K. BRAINSFit: Mutual Information Registrations of Whole-Brain 3D Images, Using the Insight Toolkit, The Insight Journal, July 2007