radxtools / topology-radiomics Goto Github PK

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• setup.py file

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Currently, the Topology Radiomics packages only supports nifty (.nii) images via nibabel.

Sometimes, the labs use the .mha or .mhd imaging formats. Could you please add SimpleITK and/or NumPy support in the compute_morphology_features function to expand imaging format compatibility?

SimpleITK example:

volume = sitk.ReadImage("/path/to/volume.mha") # vol type is SimpleITK.SimpleITK.Image
features = rad.compute_morphology_features(volume, config)

NumPy Array from SimpleITK example:

volume = sitk.ReadImage("/path/to/volume.mha")
volume_np = sitk.GetArrayFromImage(volume) # vol_np type is numpy.ndarray
features = rad.compute_morphology_features(volume_np, config)

To pass a NumPy array from SimpleITK into the compute_morphology_features function, I made the following change:

def compute_morphology_features(mri_mask_voxels: BinaryVoxelMask,
                                config: MorphologyConfig = MorphologyConfig()) -> MorphologyFeatures:
    #mask = mri_mask_voxels.mri_voxel_mask # commented this line out because NumPy array does not have this object
    mask = mri_mask_voxels

• pyvista for mesh
• scipy for marching cubes
• numpy for general data handling

Operating system - Mac OS
Python- 3.7

• Sigma value in the config object should be given in millimeters.
• Notes:
• This would make it slightly more complicated as we would need to know the x,y,z length of a voxel.
• Most MRI pictures have x and y of the same length, but the z length is normally smaller. (x == y, x > z, y > z). This is due the way the scans are taken.

Could you please add the following image to the documentation? It provides a really nice visualization of what curvature features look like.

You can find the image here.

• Neshdev repo
• bric/invent lab repo

In the documentation, could you please add a note indicating outliers are clipped on a per lesion basis? This would notify users to adjust their code accordingly.

Clipping outliers on a per lesion basis does not need to be changed. Based on conversations with the lab, this behavior is ok and is needed for viewing the meshes.

Please let me know if you need any additional information.

Thank you!

The merge labels function should be rewritten such that 0 is empty space. All other integers are labels.

0 - should be background, not min value

default behavior:
merge all other labels

• loading data is babel
• loading data is pymed
• explaing surface measures with plotly visualizations