Medical-Image-Segmentation | based framework for medical image segmentation

by Guzaiwang Python Version: Current License: Apache-2.0

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kandi X-RAY | Medical-Image-Segmentation Summary

Medical-Image-Segmentation is a Python library. Medical-Image-Segmentation has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This repo is a PyTorch-based framework for medical image segmentation, whose goal is to provide an easy-to-use framework for academic researchers to develop and evaluate deep learning models. It provides fair evaluation and comparison of CNNs and Transformers on multiple medical image datasets.

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Quality

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Support

Medical-Image-Segmentation has a low active ecosystem.

It has 1 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

Medical-Image-Segmentation has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Medical-Image-Segmentation is current.

Quality

Medical-Image-Segmentation has no bugs reported.

Security

Medical-Image-Segmentation has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

Medical-Image-Segmentation is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Medical-Image-Segmentation releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

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Medical-Image-Segmentation Key Features

No Key Features are available at this moment for Medical-Image-Segmentation.

Medical-Image-Segmentation Examples and Code Snippets

No Code Snippets are available at this moment for Medical-Image-Segmentation.

Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install Medical-Image-Segmentation

You can download it from GitHub.
You can use Medical-Image-Segmentation like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

MedFormer (Official implementation)UNet. Including 2D, 3D with different building block, e.g. double conv, Residual BasicBlock, Bottleneck, MBConv, or ConvNeXt block.UNet++Attention UNetDual AttentionTransUNetSwinUNetUNETRVT-UNetnnFormerSwinUNETRMore models are comming soon ...

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