license: mit
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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 |
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).