GitHub - skill-diver/segmentation_refiner: Addressing the limitations of deep learning methods, the algorithms and anatomical principles enable automated detection and repair of missegmentation in 3d medical image data, the repair results can reach 90% dice score (evaluated by human experts)

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Addressing the limitations of deep learning methods, the algorithms and anatomical principles enable automated detection and repair of missegmentation in 3d medical image data, the repair results can reach 90% dice score (evaluated by human experts)

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Name		Name	Last commit message	Last commit date
Latest commit History 1 Commit
sample		sample
ssm		ssm
statistics		statistics
third_party		third_party
train		train
__init__.py		__init__.py
classifier.py		classifier.py
consistency_loop.py		consistency_loop.py
environment.yml		environment.yml
eval.py		eval.py
eval.sh		eval.sh
graph.py		graph.py
identify.py		identify.py
locate.py		locate.py
metrics.py		metrics.py
readme.txt		readme.txt
regressor.py		regressor.py
requirements.txt		requirements.txt
run_test.out		run_test.out
run_test.py		run_test.py
segment_spine.py		segment_spine.py
segment_vertebra.py		segment_vertebra.py
segmentor.py		segmentor.py
test.py		test.py
utils.py		utils.py

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1. Set up environment
pip install -r requirements.txt

2. Do refinement.
python test.py -D <input_dir> -B <spine_binarymask> -S <output_dir> -P<vertebrae path which you want to refine>