BoneMet: An Open Large-Scale Multi-Modal Murine Dataset for Breast Tumor Bone Metastasis Diagnosis and Prognosis

ICLR 2025 Conference Submission12268 Authors

Keywords: Medical Dataset, Breast Tumor Bone Metastasis, Diagnosis, Prognosis, Sparse CT reconstruction, CT, X-ray, AI for Science

Abstract: Breast tumor bone metastasis (BTBM) affects women’s health globally, calling for the development of effective solutions for its diagnosis and prognosis. While the deep learning has exhibited impressive capacities across various healthcare domains, their applicability to managing BTBM diseases is consistently hindered by the lack of an open, large-scale, deep learning-ready dataset. As such, we introduce the Bone Metastasis (BoneMet) dataset, the first large-scale, publicly available, high-resolution medical resource specifically targeting BTBM for disease diagnosis, prognosis, and treatment management. It offers over 50 terabytes of multi-modal medical data, including 2D X-ray images, 3D CT scans, and detailed biological data (e.g., medical records and bone quantitative analysis), collected from thousands of mice spanning from 2019 to 2024. Our BoneMet dataset is well-organized into six components, i.e., Rotation-X-Ray, Recon-CT, Seg-CT, Regist-CT, RoI-CT, and MiceMediRec. Thanks to its extensive data samples and our tireless efforts of image processing, organization and data labeling, BoneMet can be readily adopted to build versatile, large-scale AI models for managing BTBM diseases, which have been validated by our extensive experiments via various deep learning solutions. To facilitate its easy access and wide dissemination, we have created the BoneMet package, providing three APIs that enable researchers to (i)flexibly process and download the BoneMet data filtered by specific time frames;and (ii) develop and train large-scale AI models for precise BTBM diagnosis and prognosis. The BoneMet dataset is officially available on Hugging Face Datasets at https://huggingface.co/datasets/BoneMet/BoneMet. The BoneMet package is available on the Python Package Index (PyPI) at https://pypi.org/project/BoneMet. Code and tutorials are available at https://github.com/BoneMet/BoneMet.

Primary Area: datasets and benchmarks

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Submission Number: 12268