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Downstream datasets for CVPR 2026: Foundation Models for General CT Image Diagnosis.
References:
Rahimzadeh, M., Attar, A., & Sakhaei, S. M. (2021). A fully automated deep learning-based network for detecting COVID-19 from a new and large lung CT scan dataset. Biomedical Signal Processing and Control, 102588. https://doi.org/10.1016/j.bspc.2021.102588
Peeters, D., Obreja, B., Antonissen, N., & Jacobs, C. (2025). Benchmarking of Artificial Intelligence and Radiologists for Lung Cancer Screening in CT: The LUNA25 Challenge. Medical Image Computing and Computer Assisted Intervention 2025 (MICCAI). Zenodo. https://doi.org/10.5281/zenodo.15094631
Ji, Y., Bai, H., Ge, C., Yang, J., Zhu, Y., Zhang, R., Li, Z., Zhang, L., Ma, W., Wan, X., et al. (2022). Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation. Advances in Neural Information Processing Systems, 35, 36722–36732.
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