Metadata-Version: 2.1
Name: vEMden
Version: 0.2
Summary: Volume Electron Microscopy DENoising (vEMden)
Home-page: https://www.thibault.biz/Research/VolumeEM/vEMden/vEMden.html
Download-URL: https://www.thibault.biz/Doc/vEMden/vEMden-0.2.tar.gz
Author: Guillaume THIBAULT, Katya GIANNIOS
Author-email: thibaulg@ohsu.edu
Maintainer: Guillaume THIBAULT
Maintainer-email: thibaulg@ohsu.edu
License: MIT
Keywords: Denoising,Electron Microscopy,Volume EM,vEM,FIB-SEM,Focused Ion Beam Scanning Electron Microscop
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Environment :: GPU
Classifier: Environment :: GPU :: NVIDIA CUDA :: 10.2
Classifier: Environment :: Other Environment
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Healthcare Industry
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Image Processing
Requires-Python: >=3.8,<3.10

# Volume Electron Microscropy DENoising (vEMden)

This package performs automatic (unsupervised) denoising of volume electron microscopy images. Two deep learning 
architectures are available:
<ul>
<li>Noise Reconstruction & Remove Network (NRRN)</li>
<li>DenoiseNet</li>
</ul>

For installation, more information/details and full examples with code and data, visit:
https://www.thibault.biz/Research/VolumeEM/vEMden/vEMden.html
