Datasets:
				
			
			
	
			
	
		
			
	
		
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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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            # Load the dataset
         
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            from datasets import load_dataset
         
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            # Download and load the dataset
         
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            dataset = load_dataset("wanglab/CT_DeepLesion-MedSAM2")
         
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            # Access the train split
         
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            train_dataset = dataset["train"]
         
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            # Display the first example
         
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            print(train_dataset[0])
         
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            ```
         
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            Please cite both DeepLesion and MedSAM2 when using this dataset. 
         
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            ```bash
         
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