Metadata-Version: 2.1
Name: moosez
Version: 2.2.30
Summary: An AI-inference engine for 3D clinical and preclinical whole-body segmentation tasks
Home-page: https://github.com/QIMP-Team/mooseZ
Author: Lalith Kumar Shiyam Sundar | Sebastian Gutschmayer
Author-email: Lalith.shiyamsundar@meduniwien.ac.at
License: Apache 2.0
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
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Healthcare Industry
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering :: Medical Science Apps.
Requires-Python: >=3.9
License-File: LICENSE
Requires-Dist: nnunetv2
Requires-Dist: nibabel ~=3.2.2
Requires-Dist: halo ~=0.0.31
Requires-Dist: pandas ~=1.4.1
Requires-Dist: SimpleITK ~=2.2.1
Requires-Dist: pydicom ~=2.2.2
Requires-Dist: argparse ~=1.4.0
Requires-Dist: imageio ~=2.16.1
Requires-Dist: numpy
Requires-Dist: mpire ~=2.3.3
Requires-Dist: openpyxl ~=3.0.9
Requires-Dist: matplotlib
Requires-Dist: pyfiglet ~=0.8.post1
Requires-Dist: natsort ~=8.1.0
Requires-Dist: pillow >=9.2.0
Requires-Dist: colorama ~=0.4.6
Requires-Dist: dask
Requires-Dist: rich
Requires-Dist: pandas
Requires-Dist: dicom2nifti ~=2.4.8
Requires-Dist: emoji
Requires-Dist: dask[distributed]
Requires-Dist: opencv-python

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.
