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Group-wise Registration in NAMIC-kit

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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  1. Group-wise Registration in NAMIC-kit Serdar K Balci (MIT) LillaZöllei (MGH) KinhTieu (BWH) Mert R Sabuncu (MIT) PolinaGolland (MIT)

  2. Robust Group-wise Registration • Entropy based group-wise registration • ITK implementation • Empirical Evaluation

  3. Background: Groupwise Registration • Images Transforms • Transforms: • Affine • Non-rigid using B-Splines

  4. Registering to the Mean of the Population

  5. Groupwise Registration: Congealing L . Zöllei, E. Learned-Miller, E. Grimson, W.M. Wells III. "Efficient Population Registration of 3D Data."

  6. Congealing: Intuition • If Gaussian • If also • Registering to the mean with LS metric

  7. Implementation • ITK classes • Group-wise registration using congealing • Variance • Entropy

  8. Results Before Affine BS 4 BS 8 BS 16 Entropy Variance

  9. Overlap Measures

  10. Full Term Babies Before Affine BS 4 BS 8 BS 16 BS 32

  11. Pre Term Babies Before Affine BS 4 BS 8 BS 16

  12. 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

  13. 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

  14. Congealing with Two Images • Using Parzen windows • As we only have two images • Pairwise registration using LS metric

  15. Groupwise Reg. using Pairwise Reg. • If we assume that images are independent given a subject, representative of the population

  16. Registering to the mean • We assume independence over images • and draw i.i.d. samples from each image

  17. 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

  18. Results: Congealing with Entropy Before After (B-Splines ~20mm)

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