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plumo_pytorch

nvidia-docker is needed to run the program.

Usage:

./run.sh  input output

input: an input directory containing dicom files (input/*.dcm).
output: output directory where results (HTML) are written to.

If multiple GPUs are supplied, parameter 'n_gpu' in res/patch may be modified accordingly. Changing other parameters in that file is not advised, though.

Output folder will contain sub-directories for each input sample. A HTML file will be available inside for viewing predictions. Since DICOM files are used for viewing, remotely opening the web page may be a slow process.

Intermediate results are saved to intermediate ; all predicted bounding boxes can be found in intermediate/bbox_result, but they are saved as real world coordinates.

Boxes that can be directly mapped to original images are also provided in boxes folder. They are converted from above intermediate results and non maximum suppression was applied. Pickle files in boxes correspond to valid inputs, and are of format: {str(score): [z_min, y_min, x_min, z_max, y_max, x_max]}.

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  • Python 72.3%
  • HTML 22.0%
  • Shell 3.7%
  • Dockerfile 2.0%