李珺，中国科学院大学博士研究生，主要研究方向：医疗影像分析。

学习经历

2020/09-至今，中国科学院大学，计算应用技术，博士

2017/09-2020/06，中国科学技术大学，软件工程，硕士

2012/09-2016/06，西安交通大学，计算机科学与技术，学士

学术论文

[1] Li, J., Chen, J., Tang, Y., Landman, B.A., & Zhou, S.K. (2022). Transforming medical imaging with Transformers? A comparative review of key properties, current progresses, and future perspectives. ArXiv, abs/2206.01136.

[2] Li, J., Quan, Q., & Zhou, S.K. (2022). MixCL: Pixel label matters to contrastive learning. ArXiv, abs/2203.02114.

[3] Gharleghi, R., Adikari, D., Ellenberger, K.A., Ooi, S., Ellis, C., Chen, C., Gao, R., He, Y., Hussain, R., Lee, C., Li, J., Ma, J., Nie, Z., Oliveira, B.W., Qi, Y., Skandarani, Y., Wang, X., Yang, S., Sowmya, A., &Beier, S. (2022). Automated segmentation of normal and diseased coronary arteries - The ASOCA challenge. Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society, 97, 102049 .

[4] Liu, P., Deng, Y., Wang, C., Hui, Y., Li, Q., Li, J., Luo, S., Sun, M., Quan, Q., Yang, S., Hao, Y., Xiao, H., Zhao, C., Wu, X., & Zhou, S.K. (2022). Universal Segmentation of 33 Anatomies. ArXiv, abs/2203.02098.

[5] Quan, Q., Yao, Q., Li, J., & Zhou, S.K. (2021). Which images to label for few-shot medical landmark detection? 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 20574-20584.

[6] Deng, Y., Wang, C., Hui, Y., Li, Q., Li, J., Luo, S., Sun, M., Quan, Q., Yang, S., Hao, Y., Liu, P., Xiao, H., Zhao, C., Wu, X., & Zhou, S.K. (2021). CTSpine1K: A Large-Scale Dataset for Spinal Vertebrae Segmentation in Computed Tomography. ArXiv, abs/2105.14711.

[7] Gao, R., Hou, Z., Li, J., Han, H., Lu, B., & Zhou, S.K. (2021). Joint Coronary Centerline Extraction And Lumen Segmentation From Ccta Using Cnntracker And Vascular Graph Convolutional Network. 2021 IEEE 18th International Symposium on Biomedical Imaging (ISBI), 1897-1901.

[8] Liu, P., Han, H., Du, Y., Zhu, H., Li, Y., Gu, F., Xiao, H., Li, J., Zhao, C., Xiao, L., Wu, X., & Zhou, S. (2020). Deep learning to segment pelvic bones: large-scale CT datasets and baseline models. International Journal of Computer Assisted Radiology and Surgery, 16, 749 - 756.