EMSegmenter-Tasks:Non-Human-Primate

Return to EMSegmenter Task Overview Page

Description

Non Human Primate pipeline ...TODO

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

• Root
  • Head
    • intracranial cavity (ICC)
      • White matter + Gray matter + CSF class (WGC)
        • grey matter (GM)
          • left Subcortical Gray Matter (lSGM)
            • left caudate (lCaudate)
            • left putamen (lPutamen)
            • left hippocampus (lHippocampus)
          • right Subcortical Gray Matter (rSGM)
            • right caudate (rCaudate)
            • right putamen (rPutamen)
            • right hippocampus (rHippocampus)
          • Cortical Gray Matter (CGM)
        • white matter (WM)
        • cerebrospinal fluid (CSF)
      • Brainstem
      • Cerebellum
    • background (BG)

Atlas

Image Dimension = 256 x 256 x 252
Image Spacing = 0.4688 x 0.4688 x 0.50002

Template (T1)	CSF	GM	WM

Result

Collaborators

Andriy Fedorov (BWH)

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