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# Lung Tumor 3D Segmentation - Mixed Supervision
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End to end code base for lung tumor segmentation from CT-scan using mixed supervision for deep convolutional neural network.
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## Installation
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python setupy.py install
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```
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## Docker Integration
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*To be specified*
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## Usage
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**Initiate Training:** `python .\Runable\Test\test_sevlus.py`
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In this case, the paths would also need to be updated.
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## Authors
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[Vemund Fredrksen](https://github.com/VemundFredriksen)
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## License
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[MIT](https://choosealicense.com/licenses/mit/)
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# Training code for Lung Tumor 3D Segmentation - Mixed Supervision
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End to end code base for lung tumor segmentation from CT-scan using mixed supervision for deep convolutional neural network.
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Takes 3D CT scans as input and outputs 3D segmentation of primary tumor.
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Project aims to utilize multiple different datasets with different label types (classification labels, bounding boxes, rough segmentations, and fine segmentations).
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## Installation
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python setupy.py install
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```
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## Usage
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**Initiate Training:** `python .\Runable\Test\test_sevlus.py`
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In this case, the paths would also need to be updated.
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## Authors
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[Vemund Fredrksen](https://github.com/VemundFredriksen), [Svein Ole M. Sevle](https://github.com/sosevle), & [André Pedersen](https://github.com/andreped).
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## License
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[MIT](https://choosealicense.com/licenses/mit/)
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