EMSegmenter-Tasks:LesionExp
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Description
Two channel automatic segmentation of T1 and FLAIR MRI brain scans into the major tissue classes (gray matter, white matter, csf). 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 T1 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: Assign T1 GM intensity distribution to T1 Lesion intensity distribution
- Step 5: Automatically segment the MRI scan into the structures of interest using EM Algorithm (Pohl et al 2007)
Anatomical Tree
- root
- background (BG)
- intracranial cavity (ICC)
- white matter (WM)
- grey matter (GM)
- cerebrospinal fluid (CSF)
- Lesion
Atlas
Atlas was generated based on 82 scans and corresponding segmentations provided by Psychiatry Neuroimaging Laboratory, BWH. We registered the scans to a preselected template via Warfield et al. 2001.
Image Dimension = 256 x 256 x 124
Image Spacing = 0.9375 x 0.9375 x 1.5
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| Template (T1) | CSF | GM | WM |
Result
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
