2021年6月毕业于西北大学，获得工学博士学位。2021年7月至今西北大学信息科学与技术学院讲师。CSIG数字文化遗产专业委员会委员，北京围手术期医学学会乳腺病微创及人工智能辅助诊治专委会委员，西安市科学技术学会青年人才托举计划项目获得者，人工智能赋能教育“科学家+工程师”队伍主要成员，陕西高校青年创新团队、西安市影像组学与智能感知重点实验室成员。主持国家自然科学基金青年项目1项、陕西省重点研发计划一般项目1项并参与国家自然科学基金面上项目等纵向项目7项。在光学分子影像的基础上紧追研究前沿，开展影像组学与智能感知的研究工作。长期与广东省人民医院、中山大学第一附属医院、北京协和医院开展紧密合作研究。研究成果发表在Expert. Syst. Appl.、IEEE Trans. on Biomed. Engineering、European Radiology、Rheumatology等高水平刊物上。基于以上成果获得2020 年“陕西省自然科学二等奖”，2025 年“陕西高等学校科学技术研究优秀成果一等奖和2019 年“陕西高等学校科学技术一等奖”。

主要研究领域：医学图像处理与可视化、光学分子断层成像、因果理论等方法研究。

招生专业：计算机科学与技术（学术学位硕士），电子信息(软件工程)（专业学位硕士）

欢迎感兴趣的同学加入我的科研团队！联系方式：xueleihe@nwu.edu.cn

同时欢迎本科同学联系我参加学科竞赛！

获奖

2025     陕西高等学校科学技术研究优秀成果（6/7）                      授予单位：陕西省教育厅

2020     陕西省自然科学奖二等奖（6/6）                                          授予单位：陕西省人民政府

2020     陕西高等学校科学技术奖一等奖（8/10）                            授予单位：陕西省教育厅

竞赛获奖

 

2025 Uncertainty-Guided Curriculum Learning for Automated Liver Fibrosis Staging on Heterogeneous MRI, MICCAI Challenge Toward real world medical image analysis Comprehensive Analysis & computing of REal-world medical images (CARE) 2025, Best Paper Runner-up

 

发表SCI论文情况

一作：

[1] He X, Li K, Wei R, et al. A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy[J]. La radiologia medica, 2023, 128(12): 1508-1520. (中科院JCR一区，2023 IF：8.90)

[2] He X, Wang M, Zhao C, et al. Deep learning-based automatic scoring models for the disease activity of rheumatoid arthritis based on multimodal ultrasound images[J]. Rheumatology, 2023: kead366. (中科院JCR一区，2023 IF：5.5)

[3] He X, Yu J, Wang X, et al. Half Thresholding Pursuit Algorithm for Fluorescence Molecular Tomography[J]. IEEE Transaction on Biomedical Engineering，2019, 66(5): 1468-1476. (中科院JCR二区，2019 IF：4.424)

[4] He X, Meng H, He X, et al. Nonconvex Laplacian Manifold Joint Method for Morphological Reconstruction of Fluorescence Molecular Tomography[J]. Molecular Imaging and Biology, 2020. (中科院JCR三区，2019 IF：2.925)

[5] He X, Wang X, Yi H, et al. Laplacian manifold regularization method for fluorescence molecular tomography[J]. Journal of Biomedical Optics, 2017, 22(4): 045009-045009. (中科院JCR三区，2019 IF：2.785)

通讯：

[6] Yu, J., Wang, H., Wen, Y., Chen, S., An, Y., Lu, X., & He, X#. 3D-DCASphereNet: 3D Dynamic Convolutional Attention Network with Spherical Representation for High Heterogeneity in Lung Nodule Detection[J]. Expert Systems with Applications, 2026: 131375.

[7] Wang, M., Zheng, Z., Wang, C., Fan, C., & He, X. Enhancing medical image segmentation: A self-supervised approach with global feature enhancement and edge constraint guidance. Displays,2026, 92, 103300.

[8] Wu, Y., Chen, Z., Guo, H., Li, J., Yi, H., Yu, J., ... & He, X#. Fluorescence separation based on the spatiotemporal Gaussian mixture model for dynamic fluorescence molecular tomography. Journal of the Optical Society of America A,2024: 41(10), 1846-1855.

[9] Liu, Y., Cai, S., He, X., He, X.#, & Yue, T. Construction of a Food Safety Evaluation System Based on the Factor Analysis of Mixed Data Method. Foods, 2024:13(17), 2680.

共一：

[10] Wu, Y.*, He, X.*, Chen, Z., Wei, X., Liu, Y., Li, S., ... & He, X. Group sparse-based Taylor expansion method for liver pharmacokinetic parameters imaging of dynamic fluorescence molecular tomography. Physics in Medicine & Biology,2024: 69(11), 115006.

[11] Zhao Y*, Li S*, He X*, et al. Liver injury monitoring using dynamic fluorescence molecular tomography based on a time-energy difference strategy[J]. Biomedical Optics Express, 2023, 14(10): 5298-5315. (中科院JCR二区，2023 IF：3.40)

[12] Zhao Q*, He X*, Wang K, et al. Deep learning model based on contrast-enhanced ultrasound for predicting early recurrence after thermal ablation of colorectal cancer liver metastasis[J]. European Radiology, 2022: 1-11. (中科院JCR二区，2019 IF:7.034)

[13] Ma Q*, He X*., Li K et al. Dynamic contrast-enhanced Ultrasound Radiomics for hepatocellular carcinoma recurrence prediction after thermal ablation [J]. Molecular Imaging and Biology, 2020. (中科院JCR三区，2019 IF：2.925)

其他：

[14] Zhang B, Wang K, Xu T, et al. Deep learning model for predicting the RAS oncogene status in colorectal cancer liver metastases[J]. Journal of Cancer Research and Therapeutics, 2025, 21(2): 362-370.

[15] Li S, Zhang L, Guo H, et al. CSA-FCN: Channel-and Spatial-Gated Attention Mechanism based Fully Complex-Valued Neural Network for System Matrix Calibration in Magnetic Particle Imaging[J]. IEEE Transactions on Computational Imaging, 2025.

[16] Wei D, Zhao Y, Li S, et al. RGMLN: Residual Graph Model Learning Network for Bioluminescence Tomography[J]. IEEE Transactions on Computational Imaging, 2025.

[17] Zhang H, Xu L, Yang L, et al. Deep learning-based intratumoral and peritumoral features for differentiating ocular adnexal lymphoma and idiopathic orbital inflammation[J]. European Radiology, 2025, 35(3): 1276-1289.

[18] Yuan Y, Guo H, Yu J, et al. Robust reconstruction of fluorescence molecular tomography by minimizing the capped L2, p norm[J]. Biomedical Signal Processing and Control, 2025, 109: 108021.

[19] Gao H, Li J, Wu Y, et al. Imaging-aided diagnosis and treatment based on artificial intelligence for pulmonary nodules: A review[J]. Physica Medica, 2025, 136: 105050.

[20] Zechen Z, Xuelei H, Fengjun Z, et al. PSNAS-Net: Hybrid gradient-physical optimizationfor efficient neural architecture search in customized medical imaging analysis[J]. Expert Systems with Applications, 2025, 288: 128155.

[21] Song Q, He X, Wang Y, et al. Clinical validation of AI assisted animal ultrasound models for diagnosis of early liver trauma[J]. Scientific Reports, 2025, 15(1): 22513.

[22] Zhang H, Guo H, Hou Y, et al. GAICN: Graph Attention Iterative Contraction Network for Bioluminescence Tomography[J]. IEEE Transactions on Medical Imaging, 2024.

[23] Zheng, Z., Wang, M., Fan, C., Wang, C., He, X., & He, X. Light&Fast Generative Adversarial Network for high-fidelity CT image synthesis of liver tumor. Computer Methods and Programs in Biomedicine,2024, 108252.

[24] Li, S., Wang, B., Yu, J., He, X., Guo, H., & He, X. FSMN-Net: a free space matching network based on manifold convolution for optical molecular tomography. Optics Letters, 2024:49(5), 1161-1164.

[25] Jiang X, Luo Y, He X, et al. Development and validation of the diagnostic accuracy of artificial intelligence-assisted ultrasound in the classification of splenic trauma[J]. Annals of Translational Medicine, 2022, 10(19). (中科院JCR三区，2019 IF：3.616)

[26] Xie X, Yang L, Zhao F, Wang D, Zhang H, He X, Cao X, Yi H, He X and Hou Y. A deep learning model combining multimodal radiomics, clinical and imaging features for differentiating ocular adnexal lymphoma from idiopathic orbital inflammation[J]. European Radiology, 2022: 1-11. (中科院JCR二区，2019 IF：)

[27] Zhao F, Gao P, Hu H, He X, Hou Y, and He X. Efficient Kidney Segmentation in Micro-CT Based on Multi-Atlas Registration and Random Forests[J]. IEEE Access, 2018, 99:1-1(中科院JCR二区，2019 IF：3.745)

[28] Zhao F, Chen Y, Chen F, He X, Cao X, Hou Y, Yi H*, He X *, and Liang J*. Semi-supervised Cerebrovascular Segmentation by Hierarchical Convolutional Neural Network[J]. IEEE Access, 2018, 6: 67841-67852. (中科院JCR二区，2019 IF：3.745)

发表EI论文情况

[1] 王晓东，耿国华，易黄建，何雪磊，贺小伟，基于低秩矩阵填充的背景荧光噪声抑制方法[J]. 光学学报, 2018年.（第四作者, EI收录）

[2] 王晓东，耿国华，易黄建，何雪磊，贺小伟，用于定位激发平面的混合高斯方法[J]. 激光与光电子学进展, 2018年（第四作者, EI收录）

[3] 侯榆青,胡昊文,赵凤军,何雪磊,易黄建,贺小伟，主动形状模型分割方法对光学重建影响评估[J]. 光学学报, 2017. (第四作者，EI收录)

[4] 耿国华, 何雪磊, 王美丽, 等. 文化遗产活化关键技术研究进展[J]. 中国图象图形学报, 2022, 24(6): 1988-2007. (第二作者，EI收录)

专利

[1] 贺小伟，何雪磊，易黄建，陈雁蓉，王晓东，侯榆青，宋小磊，一种基于半阈值追踪算法的荧光分子断层成像重建方法，CN201710448650.6，申请日期：2017-06-14。

[2] 赵凤军，陈雁蓉，贺小伟，贺小慧，高培，何雪磊，孙飞飞，曹欣，易黄建，侯榆青，基于统计形状模型的医学图像Graph Cut分割方法，申请号： 201610838092.X，申请日：2016-09-21。

学术会议（通讯）

[1] Hu, D., He, X.#, Zhao, F., & He, X#. TPCL: A Tri-Modal Phase-Aware Contrastive Learning Framework for Multiphase CT, Clinical Data, and Medical Text Integration[C]//2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2025: 2245-2252.

[2] Wang C, He X, Zheng Z, et al. A Dynamic Prototype Multi-Model Fusion Framework Based on a Feature Screening Mechanism[C]//2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2025: 4185-4189.

[3] Zhao Y, Zhao F, Zhang H, et al. OMGAN: One-to-Many Generative Adversarial Network for Diagnosing Orbital Lymphoproliferative Disorders in Incomplete Multi-Parametric MRI[C]//2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2025: 4471-4476.

[4] Wang C, Wang S, He X. An Improved Sine Cosine Algorithm[C]//2023 3rd International Conference on Intelligent Communications and Computing (ICC). IEEE, 2023: 248-252.

[5] Fan C, Zheng Z, Wang M, et al. The pseudo-siamese framework combines Transformer and CNN for medical image generation[C]//2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2024: 1-4.

[6] Zheng Z, Fan C, Wang C, et al. The Combine of GLCM and Group, Focuses on the Grayscale of Medical Images[C]//2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2024: 1-4.

[7] Gao H, Zhu B, Zhang S, et al. Advancing Medical Imaging: A Domain-Adaptive Approach to Distinguish Lung Cancer and Pulmonary Cryptococcosis[C]//2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2024: 1-4.

[8] Wang M, Zheng Z, Fan C, et al. Edge-Net: A Self-supervised Medical Image Segmentation Model Based on Edge Attention[C]//Chinese Conference on Pattern Recognition and Computer Vision (PRCV). Singapore: Springer Nature Singapore, 2024: 241-254.

主持科研项目情况

[1] 国家自然科学基金委员会,青年项目，62201459，面向早期肝纤维化分期的动态荧光分子断层成像关键技术研究，2023-01-01 至 2025-12-31, 30万元, 在研, 主持

[2] 陕西省重点研发计划，一般项目，2025SF-YBXM-380，肝癌肿瘤进展时序多模态影像分析技术研究，2025-06-01 至 2027-6-01, 7万元, 在研, 主持

[3] 西安市科学技术协会青年人才托举计划学习项目，0959202513085，肝癌肿瘤进展时序可信影像分析技术研究，2025-07-01 至 2027-06-01, 0.8万元, 在研, 主持

 

参与科研项目情况

[4] 国家自然科学基金委员会，面上项目，82572322，基于多中心临床影像数据的CTD-ILD多模态智能评估模型构建及应用研究，2026-01-01至2029-12-31，49万元，在研，参与

[5] 国家自然科学基金委员会，面上项目，62476218，面向不完整多模态影像的眼眶淋巴增生病可信赖诊断方法研究，2025-01-01至2028-12-31，51万元，在研，参与

[6] 国家自然科学基金委员会, 面上项目, 62271394, 面向实时近红外二区光学分子断层成像的模型驱动深度学习重建方法研究, 2023-01-01 至 2026-12-31, 55万元, 在研, 参与

[7] 国家自然科学基金委员会, 面上项目, 12271434, 基于Deep Unrolling的高分辨近红外二区荧光分子断层成像方法研究, 2023-01-01 至 2026-12-31, 46万元, 在研, 参与

邮箱 : ba49ca7a79ed74f6f64891a15aa4330d442e22dcb0028fe734844423400722c7273bf3702fd7871acdedbbaf5f5505871d15dc2ca8bf5ee3b1265adbe547d7349cbd32aa6473c9cbb7e095319799c8ef085e0e8b1e61ec9b89722cc9eb9f5890ffcdbc76176aaa1e2a39f70be580520987222b13cbef13ff350591df36d94937

[1] 2011.9 -- 2015.6
武汉大学       电子信息工程       大学本科毕业

[2] 2015.9 -- 2021.6
西北大学       计算机应用技术       博士研究生毕业       工学博士学位

[3] 2016.9 -- 2021.6
西北大学       计算机应用技术       研究生(博士)毕业       工学博士学位

[4] 2011.9 -- 2015.6
武汉大学       电子信息工程       大学本科毕业

[1] 2021.7 -- 至今
西北大学      电子信息学院（人工智能学院）      在职

[1] 2025.11 -- 至今
北京围手术期医学学会乳腺病微创及人工智能辅助诊治专委会委员

[2] 2025.7 -- 至今
CSIG数字文化遗产专业委员会委员

光学分子影像

影像组学分析