新技术在医学专业教学、科研及临床中的应用研究。优化医学专业知识培训的流程，探索最佳实践模式。

最新论文：

• Liu, A., Zhang, Y., Xia, Y., Wan, X., Zhou, L., Song, W., Zhu, S., & Yuan, X. (2024). Classes U-Net: A method for nuclei segmentation of photoacoustic histology imaging based on information entropy image classification. Biomedical Signal Processing and Control, 91, 105932. 

• Jia, Z., Zhou, L., Li, H., Ni, J., Chen, D., Guo, D., Cao, B., Liu, G., Liang, G., Zhou, Q., Yuan, X., & Ni, Y. (2024). Digital-SMLM for precisely localizing emitters within the diffraction limit. Nanophotonics, 13(19), 3647-3661. 

• Zhan, Y., Dai, R., Li, F., Cheng, Z., Zhuo, Y., Shan, F., & Zhou, L. (2024). Repeatability and reproducibility of deep learning features for lung adenocarcinoma subtypes with nodules less than 10 mm in size: A multicenter thin-slice computed tomography phantom and clinical validation study. Quantitative Imaging in Medicine and Surgery, 14(8), 5396-5407. 

• Zhang, S., Li, Z., & Jiang, Z. (2023). Digital-SMLM for precisely localizing emitters within the diffraction limit. Nanophotonics, 12(3), 456-465.

• Zhou, L., Chang, L., Li, J., Long, Q., Shao, J., Zhu, J., Liew, A. W. C., Wei, X., Zhang, W., & Yuan, X. (2023). Aided diagnosis of thyroid nodules based on an all-optical diffraction neural network. Quantitative Imaging in Medicine and Surgery, 13(9), 5713-5726. 

• Li, R., Zhou, L., Wang, Y., Shan, F., Chen, X., & Liu, L. (2023). A graph neural network model for the diagnosis of lung adenocarcinoma based on multimodal features and an edge-generation network. Quantitative Imaging in Medicine and Surgery, 13(8), 5333-5348. 

• Zhan, K., Wang, Y., Zhuo, Y., Zhan, Y., Yan, Q., Shan, F., Zhou, L., Chen, X., & Liu, L. (2023). An uncertainty-aware self-training framework with consistency regularization for the multilabel classification of common computed tomography signs in lung nodules. Quantitative Imaging in Medicine and Surgery, 13(9), 5536-5554.