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A powerful toolkit collection for medical image analysis in python. The project is created by members of ZMIC laboratory, School of Data Science, Fudan University.

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PyCAMIA

Python Computer Aided Medical Image Analysis (PyCAMIA) is a powerful toolkit collection for medical image analysis in python. The project is created by members of ZMIC laboratory, School of Data Science, Fudan University. PyCAMIA includes the following packages, please click the links to see more information.

The project is still under development, the available packages are marked with *.

All following packages can be installed by command pip install *.

  • pycamia* [@contributor: All contributors]: A foundamental package for the project. It is included in most of the packages in the project and contains some basic self-designed functions and types.
  • pyoverload* [@contributor: Yuncheng Zhou]: Overload package for python. It is consistant with Jedi auto-completion and only a simple @overload decorator is needed.
  • torchbatch [@contributor: N/A]: An easy to use extension of pytorch with tensors with a batch specifier, variables with auto device selection, modules with simple read & write API and optimizers with trivial learning rate modifier.
  • micomputing [@contributor: N/A]: A package designed for medical image computing which focus on image registration and interpolation.
  • mivisual [@contributor: N/A]: A package that provides visualization for medical images, plots, charts, progress bars, numpy data, profiles etc.

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Xiahai Zhuang: homepage

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A powerful toolkit collection for medical image analysis in python. The project is created by members of ZMIC laboratory, School of Data Science, Fudan University.

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