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Group-wise Registration in NAMIC-kit. Serdar K Balci (MIT) Lilla Zöllei (MGH) Kinh Tieu (BWH) Mert R Sabuncu (MIT) Polina Golland (MIT). Robust Group-wise Registration. Entropy based group-wise registration ITK implementation Empirical Evaluation.

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Group-wise Registration in NAMIC-kit

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Group-wise Registration in NAMIC-kit

Serdar K Balci (MIT)

LillaZöllei (MGH)

KinhTieu (BWH)

Mert R Sabuncu (MIT)

PolinaGolland (MIT)


Robust Group-wise Registration

  • Entropy based group-wise registration

  • ITK implementation

  • Empirical Evaluation


Background: Groupwise Registration

  • Images Transforms

  • Transforms:

    • Affine

    • Non-rigid using B-Splines


Registering to the Mean of the Population


Groupwise Registration: Congealing

L . Zöllei, E. Learned-Miller, E. Grimson, W.M. Wells III.

"Efficient Population Registration of 3D Data."


Congealing: Intuition

  • If Gaussian

  • If also

    • Registering to the mean with LS metric


Implementation

  • ITK classes

    • Group-wise registration using congealing

      • Variance

      • Entropy


Results

Before Affine BS 4 BS 8 BS 16

Entropy

Variance


Overlap Measures


Full Term Babies

Before Affine BS 4

BS 8 BS 16 BS 32


Pre Term Babies

Before Affine BS 4

BS 8 BS 16


Summary

  • Implemented group-wise registration in ITK

    • Congealing: Entropy based registration

    • Affine and BSpline

    • Multithreaded implementation

    • *Bspline optimization

  • Initial Evaluation

    • A population of 50 subjects

    • Used segmentation labels to evaluate


Ongoing Work

  • Finding optimal parameters

    • B-Spline mesh size,

    • # of hierarchical levels

    • Subsampling

  • Quantitative comparison to other methods

    • Pair-wise registration to the mean using MI


Congealing with Two Images

  • Using Parzen windows

  • As we only have two images

  • Pairwise registration using LS metric


Groupwise Reg. using Pairwise Reg.

  • If we assume that images are independent given a subject, representative of the population


Registering to the mean

  • We assume independence over images

  • and draw i.i.d. samples from each image


Groupwise Registration using Joint Entropy

  • Assume i.i.d over space, but don’t make any assumptions about images

  • Estimating entropy of an N-dimensional distribution is a challenging task


Results: Congealing with Entropy

Before After (B-Splines ~20mm)


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