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@@ -13,6 +13,7 @@ This dataset includes the following two compressed files:
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  - **label_192.zip**: Contains 192 volumes with pixel-level annotations (Files need to be suffixed nii.gz).
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  - You can directly download it: wget https://huggingface.co/datasets/WuBiao/BHSD/resolve/main/label_192.zip?download=true
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  - **unlabel_2000.zip**: Contains 2000 volumes of unannotated reconstructed data.
 
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  ## Applications
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  This dataset is primarily intended to support the use of deep learning techniques in medical image segmentation tasks, particularly for multi-class segmentation of intracranial hemorrhages. It can be used for supervised and semi-supervised ICH segmentation tasks, and we provide experimental results with state-of-the-art models as reference benchmarks.
 
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  - **label_192.zip**: Contains 192 volumes with pixel-level annotations (Files need to be suffixed nii.gz).
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  - You can directly download it: wget https://huggingface.co/datasets/WuBiao/BHSD/resolve/main/label_192.zip?download=true
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  - **unlabel_2000.zip**: Contains 2000 volumes of unannotated reconstructed data.
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+ - You can directly download it: wget https://huggingface.co/datasets/WuBiao/BHSD/resolve/main/unlabel_2000.zip?download=true
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  ## Applications
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  This dataset is primarily intended to support the use of deep learning techniques in medical image segmentation tasks, particularly for multi-class segmentation of intracranial hemorrhages. It can be used for supervised and semi-supervised ICH segmentation tasks, and we provide experimental results with state-of-the-art models as reference benchmarks.