杨鹤然

   助理教授,硕导

   西安交通大学

   数学与统计学院

   陕西西安 710049

   办公室:数学楼318

   邮箱:hryang@xjtu.edu.cn

  Google Scholar: https://scholar.google.com/citations?user=LX_RpsMAAAAJ&hl=en

 

教育经历

2013.09-2021.03     西安交通大学             应用数学(博士)                         导师:徐宗本

2017.09-2018.09     约翰霍普金斯大学      电气与计算机工程(访问学者)     导师:Jerry L. Prince

2009.09-2013.06     西安交通大学             理科数学实验班(学士)

 

工作经历

2021.04-至今           西安交通大学             数学与统计学院      青秀B类助理教授

 

奖励荣誉

西安交通大学第九届“十大学术新人”

西安交通大学第九届教学优秀团队奖

 

研究方向:利用机器学习解决医学影像分析中的基础问题、医学影像处理中的不确定性分析理论与方法

欢迎具有良好数学基础、编程基础,有志于从事机器学习、医学影像分析与人工智能领域研究的同学报考专硕研究生。

请有报考意向学生提前通过邮件发送简历联系。

论文发表

[1] Heran Yang, Jian Sun, et al. Learning Unified Hyper-network for Multi-modal MR Image Synthesis and Tumor Segmentation with Missing Modalities. IEEE Trans. Med. Imaging, 2023. (1区Top,领域顶刊,IF: 11.037)
[2] Heran Yang, Jian Sun, et al. Unsupervised MR-to-CT Synthesis using Structure-Constrained CycleGAN. IEEE Trans. Med. Imaging, 2020, 39(12): 4249-4261.  (1区Top,领域顶刊,IF: 11.037)
[3] Heran Yang, Jian Sun, et al. Neural Multi-atlas Label Fusion: Application to Cardiac MR Images, Med. Image Anal., 2018, 49: 60-75.  (1区Top,领域顶刊,IF: 13.828)
[4] Heran Yang, Jian Sun, et al.  A Unified Hyper-GAN Model for Unpaired Multi-contrast MR Image Translation. In MICCAI 2021.  (领域顶会)
[5] Heran Yang, Jian Sun, et al. Deep Fusion Net for Multi-atlas Segmentation: Application to Cardiac MR Images. In MICCAI 2016.  (Oral,领域顶会)
[6] Heran Yang, Jian Sun, et al. Unpaired Brain MR-to-CT Synthesis using a Structure-Constrained CycleGAN. In Deep Learning in Medical Image Analysis (DLMIA) in MICCAI 2018. 174-182.  (领域顶会Workshop)

[7] Jiazhen Wang, Yan Yang, Heran Yang, et al. MD-GraphFormer: A Model-Driven Graph Transformer for Fast Multi-Contrast MR Imaging. IEEE Trans. on Comp. Imaging, 2023.
[8] Zechen Zhao, Heran Yang, et al. Modality-Adaptive Feature Interaction for Brain Tumor Segmentation with Missing Modalities. In MICCAI 2022.  (领域顶会)

[9] Ruixia Cui, Wenbo Hua, Kai Qu, Heran Yang, et al. An Interpretable Early Dynamic Sequential Predictor for Sepsis-Induced Coagulopathy Progression in the Real-World Using Machine Learning. Frontiers in Medicine 8 (2021): 775047.
[10] Yan Yang, Na Wang, Heran Yang, et al. Model-driven Deep Attention Network for Ultra-fast Compressive Sensing MRI Guided by Cross-contrast MR Image. In MICCAI 2020.  (领域顶会)