artorg-unibe-ch/qam

Library to compute 3D surface-distances for evaluating liver ablation/tumor completeness based on segmentation images.

Quantitative Ablation Margin (QAM)

Library to compute 3D surface-distances between a tumor and an ablation volume.

You can find more about ablation treatments for liver cancer in the following open access book chapter "Stereotactic Image-Guidance for Ablation of Malignant Liver Tumors" from Liver Pathology.

We used an adapted Dice Soerensen coefficient to evaluate the ablation completeness in treating liver tumors. The quantitative ablation margin (QAM) calculation is illustrated in the next figure. The output is an array of 3D surface distances that can also be visualized as traffic-light colored histogram (see last step in the pipeline).

Installation

The library can be installed via pip from the GitHub repository

python -m pip install git+https://github.com/artorg-unibe-ch/qam.git

Usage

To calculate the ablation margin one needs a segmentation mask of the tumor, ablation, and (optional) liver. All images need to be in the same spacing, and co-registered.

Usage on the command line

python -m qam -t tumor_file -a ablation_file -l liver_file -om output_filename -p patient_id

Usage in own code

Import the packages

from qam import margin, plotting, visualization

Calculate the ablation margin:

distances = margin.compute_distances(tumor, ablation, liver, spacing_mm)
df = margin.summarize(subject_id, lesion_id, distances)

Plot the margin as a histogram:

non_ablated, insuffieciently_ablated, completely_ablated =\
plotting.plot_histogram_surface_distances(pat_name=patient_id, lesion_id=lesion_id,
                                            output_file=output_file_png,
                                            distance_map=surface_distance['distances_gt_to_pred'],
                                            title='Quantitative Ablation Margin',
                                            print_case_details=True)

To visualize the margin in 3D, the NIFTI files can be passed directly:

visualization.visualize_3d_margin(tumor_nii, ablation_nii, output_file_wrl)

With automation like Snakemake

It is possible to use the code in an automated way. An example using Snakemake is provided in the examples.

qam's Issues

Contour sphere

Add picture for surface distances pipeline

Image SMWA

np.bool support dropped on numpy 1.24.0

Hello,
I am trying to use this package in my code. I am using numpy 1.24.1 and I get the following error:

"AttributeError: module 'numpy' has no attribute 'bool'".

Apparently (NVIDIA/TensorRT#2557) numpy.bool is no longer supported, so I had to install numpy 1.23 and it now seems to work.

You may want to update the code for other users.

Thank you.