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GSoC 2020 Final Code Submission

Project link — MRI Registration using Deep Learning and Implementation of Thin-Plate Splines
Organization — INCF and DIPY

Weekly Progress

  • Community Bonding + Week 1

    • Developed a POC for non-rigid image registration using the MNIST dataset. Colab notebook
    • Made a pull request for the same. PR: dipy/dipy#2137
    • Cleaned the code and refashioned the dipy.nn.registration API
    • Added docstrings and comments.
  • Week 2

    • Implemented the VoxelMorph model (CVPR 2018). But yet to be trained. Paper
    • Implemented and trained 2D and 3D deep learning models for unsupervised affine registration. Similar to AIRNet but trained in an unsupervised fashion like the VoxelMorph model.
  • Week 3

    • Tested the VoxelMorph model on the sample data (150 T1-weighted images) that was provided. The results were very good.
    • Cleaned the code and tested the new dipy.nn.registration API that was refashioned in the first week. Colab notebook
  • Week 4

  • Evaluation 1 Week

    • Tested the VoxelMorph model on a few T2-weighted volumes from the OASIS dataset.
  • Week 5

    • Tried the VoxelMorph model for cross-modality registration (T1w static image and T2w moving images). Results weren't good.
  • Week 6

    • Retrained the cross-modality registration model with better brain segmented T2 images. The brain mask was obtained using T1s insterad of T2s. So I rigid registered T1s with T2s and got the brain masks using T1s. Still the results were bad.
    • Implemented thin-plate splines. GitHub repo
  • Week 7

  • Week 8 + Evaluation 2 Week + Week 9

    • Tried the SyN algorithm for cross-modality registration. Results looked good but the ventricular regions were expanding.
    • Discussed doubts in N3 paper
  • Week 10 and 11

    • Implemented N3 paper. But yet to be tested
    • Refashioned and cleaned the PR dipy/dipy#2137
    • Tried the SyN algorithm with more iterations. Results got worse.
  • Week 12

    • Blogs and codes
    • Documenting the whole work

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