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  [DeepLesion](https://nihcc.app.box.com/v/DeepLesion) dataset contains 32,735 diverse lesions in 32,120 CT slices from 10,594 studies of 4,427 unique patients. Each lesion has a bounding box annotation on the key slice, which is derived from the longest diameter and longest
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  perpendicular diameter. We annotated 5000 lesions with [MedSAM2](https://github.com/bowang-lab/MedSAM2) in a human-in-the-loop pipeline.
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  Please cite both DeepLesion and MedSAM2 when using this dataset.
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  ```bash
 
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  [DeepLesion](https://nihcc.app.box.com/v/DeepLesion) dataset contains 32,735 diverse lesions in 32,120 CT slices from 10,594 studies of 4,427 unique patients. Each lesion has a bounding box annotation on the key slice, which is derived from the longest diameter and longest
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  perpendicular diameter. We annotated 5000 lesions with [MedSAM2](https://github.com/bowang-lab/MedSAM2) in a human-in-the-loop pipeline.
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+ ```py
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+ # Install required package
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+ pip install datasets
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+
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+ # Load the dataset
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+ from datasets import load_dataset
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+
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+ # Download and load the dataset
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+ dataset = load_dataset("wanglab/CT_DeepLesion-MedSAM2")
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+
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+ # Access the train split
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+ train_dataset = dataset["train"]
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+
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+ # Display the first example
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+ print(train_dataset[0])
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+ ```
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+
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  Please cite both DeepLesion and MedSAM2 when using this dataset.
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  ```bash