孙亮，副研究员。入选江苏省333高层次人才培养工程。中国图象图形学学会脑图谱专业委员会委员。于2020年获得南京航空航天大学计算机科学与技术博士学位（导师：张道强教授），博士研究生期间在美国北卡罗来纳大学教堂山分校进行为期一年的联合博士培养。主要研究方向为深度学习、医学图像分析。目前，已在相关研究领域发表学术论文多篇，包括IEEE Transactions on Image Processing、IEEE Transactions on Medical Imaging、IEEE Journal of Biomedical and Health Informatics、NeuroImage等，2篇入选ESI高被引论文。主持国家自然科学基金面上项目和青年项目。博士论文“基于多图谱的脑MR图像分割研究”获江苏省优秀博士学位论文奖。作为项目负责人的“基于人工智能技术实现阿尔茨海默病个性化风险预测、早期识别和预防性干预”项目获第一届全国博士后创新创业大赛银奖，并获“全国创新创业优秀博士后”称号。

持续招收2025级计算机科学与技术、计算机技术、软件工程专硕研究生，请发邮件附送简历联系 sunl@nuaa.edu.cn

学术专著：

张道强、孙亮、接标、郝小可，脑影像智能分析，科学出版社，2025 （国家科学技术学术著作出版基金资助出版）

部分代表性成果：

1.Junyong Zhao, Liang Sun#, Dingwei Fan, Kun Wang, Haipeng Si, Huazhu Fu#, Daoqiang Zhang#. Uncertainty-driven edge prompt generation network for medical image segmentation. IEEE Transactions on Medical lmaging, 2025. (中科院一区，通讯作者)

2.Dingwei Fan, Junyong Zhao, Chunlin Li, Xinlong Wang, Ronghan Zhang, Qi Zhu, Mingliang Wang, Haipeng Si#, Daoqiang Zhang#, Liang Sun#. MA-SAM: A multi-atlas guided SAM using pseudo mask prompts without manual annotation for spine image segmentation. IEEE Transactions on Medical lmaging, 2025. (中科院一区，通讯作者)

3.Liang Sun, Yanling Fu, Junyong Zhao, Wei Shao, Qi Zhu, Daoqiang Zhang. MAS-CL: An end-to-end multi-atlas supervised contrastive learning framework for brain ROI segmentation. IEEE Transactions on Image Processing, 2024, 33: 4319-4333. (中科院一区, CCF A)

4.Junyong Zhao, Liang Sun#, Zhi Sun, Xin Zhou, Haipeng Si#, Daoqiang Zhang#. MSEF-Net: Multi-scale edge fusion network for lumbosacral plexus segmentation with MR image. Artificial Intelligence in Medicine, 2024, 148: 102771. (中科院一区，通讯作者)

5.Liang Sun, Wei Shao, Qi Zhu, Meiling Wang, Gang Li, Daoqiang Zhang. Multi-scale multi-hierarchy attention convolutional neural network for fetal brain extraction, Pattern Recognition, 2023, 133: 109029-109029. (中科院一区)

6.Junyong Zhao, Liang Sun#, Xin Zhou, Shuo Huang, Haipeng Si#, Daoqiang Zhang#. Residual-atrous attention network for lumbosacral plexus segmentation with MR image. Computerized Medical Imaging and Graphics, 2022, 100: 102109.  (通讯作者)

7.Wenyong Zhu*, Liang Sun*, Jiashuang Huang, Liangxiu Han, Daoqiang Zhang. Dual attention multi-instance deep learning for Alzheimer’s disease diagnosis with structural MRI. IEEE Transactions on Medical Imaging, 2021, 40(9): 2354-2366.(中科院一区，共同一作, Highly cited paper)

8.Liang Sun, Zhanhao Mo, Fuhua Yan, Liming Xia, Fei Shan, Zhongxiang Ding, Bin Song, Wanchun Gao, Wei Shao, Feng Shi, Huan Yuan, Huiting Jiang, Dijia Wu, Ying Wei, Yaozong Gao, He Sui, Daoqiang Zhang, Dinggang Shen. Adaptive feature selection guided deep forest for COVID-19 classification with chest CT. IEEE Journal of Biomedical and Health Informatics, 2020, 24(10): 2798-2805.(中科院一区)

9.Liang Sun, Wei Shao, Daoqiang Zhang, Mingxia Liu. Anatomical attention guided deep networks for ROI segmentation of brain MR images. IEEE Transactions on Medical Imaging, 39(6): 2000-2012.(中科院一区)

10.Liang Sun, Wei Shao, Mingliang Wang, Daoqiang Zhang, Mingxia Liu. High-order feature learning for multi-atlas based label fusion: Application to brain segmentation with MRI, IEEE Transactions on Image Processing, 2020, 29: 2702-2713. (中科院一区, CCF A)

11.Liang Sun, Daoqiang Zhang, Chunfeng Lian, Li Wang, Zhengwang Wu, Wei Shao, Weili Lin, Dinggang Shen, Gang Li, UNC/UMN Baby Connectome Project Consortium. Topological correction of infant white matter surfaces using anatomically constrained convolutional neural network, NeuroImage, 2019, 198: 114-124. (中科院一区)

12.Liang Sun, Chen Zu, Wei Shao, Junye Guang, Daoqiang Zhang, Mingxia Liu. Reliability-based robust multi-atlas label fusion for brain MRI segmentation. Artificial Intelligence in Medicine, 2019, 96: 12-24. (中科院一区)

更多信息查看：https://scholar.google.com/citations?user=o5o0q98AAAAJ&hl=zh-CN

主持科研项目：

国家自然科学基金面上项目，2024-2027

国家自然科学基金青年项目，2020-2023

广东省自然科学基金面上项目，2024-2026

中国博士后科学基金第14批特别资助（站中）

中国博士后科学基金第70批面上资助

江苏省博士后科研资助计划