arXiv Open Access 2026

Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development

Zhongying Deng Cheng Tang Ziyan Huang Jiashi Lin Ying Chen +122 lainnya

Lihat Sumber

Abstrak

Foundation models have demonstrated remarkable success across diverse domains and tasks, primarily due to the thrive of large-scale, diverse, and high-quality datasets. However, in the field of medical imaging, the curation and assembling of such medical datasets are highly challenging due to the reliance on clinical expertise and strict ethical and privacy constraints, resulting in a scarcity of large-scale unified medical datasets and hindering the development of powerful medical foundation models. In this work, we present the largest survey to date of medical image datasets, covering over 1,000 open-access datasets with a systematic catalog of their modalities, tasks, anatomies, annotations, limitations, and potential for integration. Our analysis exposes a landscape that is modest in scale, fragmented across narrowly scoped tasks, and unevenly distributed across organs and modalities, which in turn limits the utility of existing medical image datasets for developing versatile and robust medical foundation models. To turn fragmentation into scale, we propose a metadata-driven fusion paradigm (MDFP) that integrates public datasets with shared modalities or tasks, thereby transforming multiple small data silos into larger, more coherent resources. Building on MDFP, we release an interactive discovery portal that enables end-to-end, automated medical image dataset integration, and compile all surveyed datasets into a unified, structured table that clearly summarizes their key characteristics and provides reference links, offering the community an accessible and comprehensive repository. By charting the current terrain and offering a principled path to dataset consolidation, our survey provides a practical roadmap for scaling medical imaging corpora, supporting faster data discovery, more principled dataset creation, and more capable medical foundation models.

Topik & Kata Kunci

cs.CV cs.AI

Penulis (127)

Zhongying Deng

Cheng Tang

Ziyan Huang

Jiashi Lin

Ying Chen

Junzhi Ning

Chenglong Ma

Jiyao Liu

Wei Li

Yinghao Zhu

Shujian Gao

Yanyan Huang

Sibo Ju

Yanzhou Su

Pengcheng Chen

Wenhao Tang

Tianbin Li

Haoyu Wang

Yuanfeng Ji

Hui Sun

Shaobo Min

Liang Peng

Feilong Tang

Haochen Xue

Rulin Zhou

Chaoyang Zhang

Wenjie Li

Shaohao Rui

Weijie Ma

Xingyue Zhao

Yibin Wang

Kun Yuan

Zhaohui Lu

Shujun Wang

Jinjie Wei

Lihao Liu

Dingkang Yang

Lin Wang

Yulong Li

Haolin Yang

Yiqing Shen

Lequan Yu

Xiaowei Hu

Yun Gu

Yicheng Wu

Benyou Wang

Minghui Zhang

Angelica I. Aviles-Rivero

Qi Gao

Hongming Shan

Xiaoyu Ren

Fang Yan

Hongyu Zhou

Haodong Duan

Maosong Cao

Shanshan Wang

Bin Fu

Xiaomeng Li

Zhi Hou

Chunfeng Song

Lei Bai

Yuan Cheng

Yuandong Pu

Xiang Li

Wenhai Wang

Hao Chen

Jiaxin Zhuang

Songyang Zhang

Huiguang He

Mengzhang Li

Bohan Zhuang

Zhian Bai

Rongshan Yu

Liansheng Wang

Yukun Zhou

Xiaosong Wang

Xin Guo

Guanbin Li

Xiangru Lin

Dakai Jin

Mianxin Liu

Wenlong Zhang

Qi Qin

Conghui He

Yuqiang Li

Ye Luo

Nanqing Dong

Jie Xu

Wenqi Shao

Bo Zhang

Qiujuan Yan

Yihao Liu

Jun Ma

Zhi Lu

Yuewen Cao

Zongwei Zhou

Jianming Liang

Shixiang Tang

Qi Duan

Dongzhan Zhou

Chen Jiang

Yuyin Zhou

Yanwu Xu

Jiancheng Yang

Shaoting Zhang

Xiaohong Liu

Siqi Luo

Yi Xin

Chaoyu Liu

Haochen Wen

Xin Chen

Alejandro Lozano

Min Woo Sun

Yuhui Zhang

Yue Yao

Xiaoxiao Sun

Serena Yeung-Levy

Xia Li

Jing Ke

Chunhui Zhang

Zongyuan Ge

Ming Hu

Jin Ye

Zhifeng Li

Yirong Chen

Yu Qiao

Junjun He

Format Sitasi

APA MLA BibTeX

Deng, Z., Tang, C., Huang, Z., Lin, J., Chen, Y., Ning, J. et al. (2026). Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development. https://arxiv.org/abs/2603.27460

@article{deng2026, author = {Zhongying Deng and Cheng Tang and Ziyan Huang and Jiashi Lin and Ying Chen and Junzhi Ning and Chenglong Ma and Jiyao Liu and Wei Li and Yinghao Zhu and Shujian Gao and Yanyan Huang and Sibo Ju and Yanzhou Su and Pengcheng Chen and Wenhao Tang and Tianbin Li and Haoyu Wang and Yuanfeng Ji and Hui Sun and Shaobo Min and Liang Peng and Feilong Tang and Haochen Xue and Rulin Zhou and Chaoyang Zhang and Wenjie Li and Shaohao Rui and Weijie Ma and Xingyue Zhao and Yibin Wang and Kun Yuan and Zhaohui Lu and Shujun Wang and Jinjie Wei and Lihao Liu and Dingkang Yang and Lin Wang and Yulong Li and Haolin Yang and Yiqing Shen and Lequan Yu and Xiaowei Hu and Yun Gu and Yicheng Wu and Benyou Wang and Minghui Zhang and Angelica I. Aviles-Rivero and Qi Gao and Hongming Shan and Xiaoyu Ren and Fang Yan and Hongyu Zhou and Haodong Duan and Maosong Cao and Shanshan Wang and Bin Fu and Xiaomeng Li and Zhi Hou and Chunfeng Song and Lei Bai and Yuan Cheng and Yuandong Pu and Xiang Li and Wenhai Wang and Hao Chen and Jiaxin Zhuang and Songyang Zhang and Huiguang He and Mengzhang Li and Bohan Zhuang and Zhian Bai and Rongshan Yu and Liansheng Wang and Yukun Zhou and Xiaosong Wang and Xin Guo and Guanbin Li and Xiangru Lin and Dakai Jin and Mianxin Liu and Wenlong Zhang and Qi Qin and Conghui He and Yuqiang Li and Ye Luo and Nanqing Dong and Jie Xu and Wenqi Shao and Bo Zhang and Qiujuan Yan and Yihao Liu and Jun Ma and Zhi Lu and Yuewen Cao and Zongwei Zhou and Jianming Liang and Shixiang Tang and Qi Duan and Dongzhan Zhou and Chen Jiang and Yuyin Zhou and Yanwu Xu and Jiancheng Yang and Shaoting Zhang and Xiaohong Liu and Siqi Luo and Yi Xin and Chaoyu Liu and Haochen Wen and Xin Chen and Alejandro Lozano and Min Woo Sun and Yuhui Zhang and Yue Yao and Xiaoxiao Sun and Serena Yeung-Levy and Xia Li and Jing Ke and Chunhui Zhang and Zongyuan Ge and Ming Hu and Jin Ye and Zhifeng Li and Yirong Chen and Yu Qiao and Junjun He}, title = {Project Imaging-X: A Survey of 1000+ Open-Access Medical Imaging Datasets for Foundation Model Development}, year = {2026}, journal = {arXiv}, url = {https://arxiv.org/abs/2603.27460}, }

Akses Cepat

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2026
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓