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3d Slicer Extension Python Packages

Python packages with the GitHub topic 3d-slicer-extension. Sorted by monthly downloads, with stars and forks.
ccipd
collageradiomics

Python Implementation of the CoLlAGe radiomics descriptor. CoLlAGe captures subtle anisotropic differences in disease pathologies by measuring entropy of co-occurrences of voxel-level gradient orientations on imaging computed within a local neighborhood.

2K 20 12
Project-MONAI
monailabel-weekly

MONAI Label is an intelligent open source image labeling and learning tool.

1K 898 271
Project-MONAI
monailabel

MONAI Label is an intelligent open source image labeling and learning tool.

1K 898 271
KitwareMedical
slicer-layer-dm

A 3D Slicer extension introducing a new displayable manager architecture for layered rendering and interaction handling.

851 4 2
KitwareMedical
slicer-layer-dm-sdk

A 3D Slicer extension introducing a new displayable manager architecture for layered rendering and interaction handling.

326 4 2
radxtools
collageradiomicstypes

Python Implementation of the CoLlAGe radiomics descriptor. CoLlAGe captures subtle anisotropic differences in disease pathologies by measuring entropy of co-occurrences of voxel-level gradient orientations on imaging computed within a local neighborhood.

154 20 13
radxtools
collageradiomics-types

Python Implementation of the CoLlAGe radiomics descriptor. CoLlAGe captures subtle anisotropic differences in disease pathologies by measuring entropy of co-occurrences of voxel-level gradient orientations on imaging computed within a local neighborhood.

91 20 13
radxtools
collageradiomicscli

Python Implementation of the CoLlAGe radiomics descriptor. CoLlAGe captures subtle anisotropic differences in disease pathologies by measuring entropy of co-occurrences of voxel-level gradient orientations on imaging computed within a local neighborhood.

65 20 13
ccipd
collageradiomics-core

Python Implementation of the CoLlAGe radiomics descriptor. CoLlAGe captures subtle anisotropic differences in disease pathologies by measuring entropy of co-occurrences of voxel-level gradient orientations on imaging computed within a local neighborhood.

63 20 12
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