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Datasets:
aagatti
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ShapeMedKnee

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Resource Link
Model ShapeMedKnee Model
NSM Model Code GitHub Repository for NSM
Example Implementation GitHub Repository for ShapeMedKnee Example
Paper ShapeMedKnee medRxiv Paper
Description of image

This dataset was created to enable the development and testing of models of 3D anatomy. Baseline DESS knee MRIs from the Osteoarthritis Initiative (OAI) were autosegmented using a previously developed algorithm Gatti & Maly 2021. These segmentations were post-processed to create 3D models of the femur bone and cartilage using pyMSKT.

Instructions on how to download the data, fit a neural shape model (NSM) with the data, do inference using a shared model, and perform tests are provided at: https://github.com/gattia/shapemedknee.

Check back soon for the associated publication.

The data are structured as: 

/meshes
  /train
    /subfolder_X
      subjectid_LEG_fem_cart.vtk
      subjectid_LEG_femur.vtk
      ...
  /val
    /subfolder_X
      subjectid_LEG_fem_cart.vtk
      subjectid_LEG_femur.vtk
      ...
  /test
    /subfolder_X
      subjectid_LEG_fem_cart.vtk
      subjectid_LEG_femur.vtk
      ...
  /segs
    subjectid_LEG-labl.nii.gz
prediction_dataset.csv

The /meshes & /segs folders include the data used to train and test surface mesch reconstructions. The prediction_dataset.csv includes information needed for clinical prediction tasks (e.g., osteoarthritis grading, future knee replacement prediction).

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