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wanglab/CT_DeepLesion-MedSAM2

CT_DeepLesion-MedSAM2 Dataset Authors Jun Ma* 1,2, Zongxin Yang* 3, Sumin Kim2,4,5, Bihui Chen2,4,5, Mohammed Baharoon2,3,5, Adibvafa Fallahpour2,4,5, Reza Asakereh4,7, Hongwei Lyu4, Bo Wang† 1,2,4,5,6 * Equal contribution     † Corresponding author 1AI Collaborative Centre, University Health Network, Toronto… See the full description on the dataset page: https://huggingface.co/datasets/wanglab/CT_DeepLesion-MedSAM2.

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CT_DeepLesion-MedSAM2 Dataset

Authors

<a href="https://scholar.google.com.hk/citations?hl=en&user=bW1UV4IAAAAJ&viewop=listworks&sortby=pubdate">Jun Ma</a> 1,2, <a href="https://scholar.google.com/citations?user=8IE0CfwAAAAJ&hl=en">Zongxin Yang</a> 3, Sumin Kim2,4,5, Bihui Chen2,4,5, <a href="https://scholar.google.com.hk/citations?user=U-LgNOwAAAAJ&hl=en&oi=sra">Mohammed Baharoon</a>2,3,5, <a href="https://scholar.google.com.hk/citations?user=4qvKTooAAAAJ&hl=en&oi=sra">Adibvafa Fallahpour</a>2,4,5, <a href="https://scholar.google.com.hk/citations?user=UlTJ-pAAAAAJ&hl=en&oi=sra">Reza Asakereh</a>4,7, Hongwei Lyu4, <a href="https://wanglab.ai/index.html">Bo Wang</a>† 1,2,4,5,6

* Equal contribution     † Corresponding author

1AI Collaborative Centre, University Health Network, Toronto, Canada 2Vector Institute for Artificial Intelligence, Toronto, Canada 3Department of Biomedical Informatics, Harvard Medical School, Harvard University, Boston, USA 4Peter Munk Cardiac Centre, University Health Network, Toronto, Canada 5Department of Computer Science, University of Toronto, Toronto, Canada 6Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada 7Roche Canada and Genentech

About

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 perpendicular diameter. We annotated 5000 lesions with MedSAM2 in a human-in-the-loop pipeline.

# Install required package
pip install datasets

# Load the dataset
from datasets import load_dataset

# Download and load the dataset
dataset = load_dataset("wanglab/CT_DeepLesion-MedSAM2")

# Access the train split
train_dataset = dataset["train"]

# Display the first example
print(train_dataset[0])

Please cite both DeepLesion and MedSAM2 when using this dataset.

bash

@article{DeepLesion,
  title={DeepLesion: automated mining of large-scale lesion annotations and universal lesion detection with deep learning},
  author={Yan, Ke and Wang, Xiaosong and Lu, Le and Summers, Ronald M},
  journal={Journal of Medical Imaging},
  volume={5},
  number={3},
  pages={036501--036501},
  year={2018}
}

@article{MedSAM2,
    title={MedSAM2: Segment Anything in 3D Medical Images and Videos},
    author={Ma, Jun and Yang, Zongxin and Kim, Sumin and Chen, Bihui and Baharoon, Mohammed and Fallahpour, Adibvafa and Asakereh, Reza and Lyu, Hongwei and Wang, Bo},
    journal={arXiv preprint arXiv:2504.63609},
    year={2025}
}