BoneMet 0.0.2

Coming Soon!

# MedNerf with BoneMet

Training Med-Nerf with BoneMet data

See the mednerf repository for more specific details and instructions on using the medNerf model.

To train mednerf with BoneMet data, first download training data here. To prepare the data for training, crop each image to a 128x128 .png image that contains each tibia. Store all images in mednerf/graf-main/data/knee_xrays. In the graf-main directory, execute this command:

python train.py configs/knee.yaml

We reccomend training to 100,000 iterations.

Generating a reconstruction with Med-Nerf

After training the model you can generate 3D-aware CT projections with a given X-Ray. First, in render_xray_G.py, change the file path parameter in variable target_xray in line 158 to the path of the desired x-ray. Create a reconstruction with the command:

python render_xray_G.py configs/knee.yaml / --save_dir="./renderings" / --model model_best.pt / --save_every 25 / --psnr_stop 25

To change the quality of the reconstruction, increase the psnr threshold.

The reconstruction output will be in the form of a .mp4 located in graf-main/results/knee_all_360/renderings.

Acknowledgements

This code orginates from the mednerf repository. Thank you to the creators who worked hard on this model!