moosez


Namemoosez JSON
Version 3.0.11 PyPI version JSON
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home_pagehttps://github.com/ENHANCE-PET/MOOSE
SummaryAn AI-inference engine for 3D clinical and preclinical whole-body segmentation tasks
upload_time2025-01-29 18:51:35
maintainerNone
docs_urlNone
authorLalith Kumar Shiyam Sundar | Sebastian Gutschmayer | Manuel Pires
requires_python>=3.9
licenseGPLv3
keywords moosez model-zoo nnunet medical-imaging tumor-segmentation organ-segmentation bone-segmentation lung-segmentation muscle-segmentation fat-segmentation vessel-segmentation vertebral-segmentation rib-segmentation preclinical-segmentation clinical-segmentation
VCS
bugtrack_url
requirements nnunetv2 halo SimpleITK pydicom argparse numpy openpyxl pyfiglet natsort colorama dask rich pandas dicom2nifti emoji requests psutil scipy nibabel
Travis-CI No Travis.
coveralls test coverage No coveralls.
            mooseZ is an AI-inference engine based on nnUNet, designed for 3D clinical and preclinical whole-body segmentation tasks. It serves models tailored towards different modalities such as PET, CT, and MR. mooseZ provides fast and accurate segmentation results, making it a reliable tool for medical imaging applications.

            

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