3dphoto landmarking

This is a repository for Geometric learning and statistical modeling for surgical outcomes evaluation in craniosynostosis using 3D photogrammetry.. This repository contains two models as described in the manuscript.

1. Automated craniofacial landmarking model, stored as a TorchScript jit file and found in data/CraniofacialLandmarkingModel.dat.
2. Normative model of head surface development, stored as a Shelve and found in NormativePCAModel/PCAModel.dat

Dependencies:

Dependencies for this model can be found in the Requirements.txt file. Once Python is installed, install the requirements with:

python -m pip install -r Requirements.txt

Using the code

To calculate the Craniosynostosis Risk Score and the Head Shape Anomaly Index for a given 3D photogram, use the following code:

python Analyze3DPhotogram.py --input_filename "/path/to/input/3Dphotogram.vtp" --age AGE_OF_PATIENT_IN_DAYS --sex M_FOR_MALE_F_FOR_FEMALE

Due to data privacy agreements, we are not able to share any example data. To run this code, you will need an image in VTK PolyData format (.vtp) containing the entire head and face that is cropped around the mid-neck. If your data is not cropped and includes the shoulders of the patient, you should use the cropping functionality by enabling the --crop_data flag. This model was trained on data collected using a 3DMD-Head system.

Quick summary

Input: VTK PolyData file.

Output: Craniosynostosis risk score (0%-100%) and Head Shape Anomaly Index.

Troubleshooting

• Example code will not run:

  • Be sure you have not altered the "CraniofacialLandmarkingModel.dat" file in any way.
  • Be sure that you are trying to load a valid VTK PolyData file.
  • Be sure that you have installed the required dependencies as noted in the Dependencies section.

• Landmarks are not placed correctly:

  • To evaluate the landmark accuracy, run the testing script with the following:

  python TestLandmarkingModel --input_filename "/path/to/input/3Dphotogram.vtp"

  This script will save the landmarks and photogram (including any cropping) to folder containing your input photogram. If the landmarks do not look accurate, adjust the cropping flag with --crop_data. If the data is not properly cropped, adjust the percentage option using the --crop_percentage flag.

  • If the problem persists, your data may be something we have not seen before! If possible, please email the corresponding author (connor.2.elkhill@cuanschutz.edu) so that we may evaluate.

• Photogram processing takes a long time:

  • You can profile each step of this analysis using the following command:

  python ProfileAnalysisPipeline.py --input_filename "/path/to/input/3Dphotogram.vtp" --age AGE_OF_PATIENT_IN_DAYS --sex M_FOR_MALE_F_FOR_FEMALE

Any other questions? Please email the corresponding author Connor Elkhill at connor.2.elkhill@cuanschutz.edu