drkostas/3D-Semantic-Segmentation
Semantic Segmentation with Transformers on 3D Medical Images
This project helps deep learning researchers and students develop and test semantic segmentation models specifically for 3D medical images. It takes raw 3D medical image data as input and produces a segmented version of the image, where different anatomical structures or regions of interest are precisely outlined. The primary users are academic researchers or students in deep learning courses focusing on medical image analysis.
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Use this if you are a deep learning researcher or student who needs to experiment with transformer-based semantic segmentation models on 3D medical image datasets.
Not ideal if you need an out-of-the-box application for clinical diagnosis or a tool for general 2D image segmentation.
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67
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8
Language
Jupyter Notebook
License
Apache-2.0
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Last pushed
Dec 30, 2022
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