个人简介

陈昱莅，博士，副教授，硕士生导师。主要研究方向为智能数字病理图像诊断模型及预后风险预测研究。2001年9月至2005年6月获兰州大学电子信息科学与技术专业理学学士学位。2011年12月获兰州大学“无线电物理”专业理学博士学位。2012年2月获韩国科学与技术研究院（KIST）“人机交互与机器人学”专业工学博士学位。2012年7月至今，在皇冠体育博彩 从事科研和教学工作。2020年由国家留学基金委公派，赴美国凯斯西储大学计算成像与个性化诊断中心(CCIPD)交流访学。在IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Neural Networks，USCAP美国加拿大病理学会年会（病理学界最具影响力的国际学术组织之一）等重要期刊和会议上发表学术论文多篇。主持国家自然科学基金项目1项、中央高校基本科研业务费专项资金项目2项、国际合作项目1项、现代教学技术教育部重点实验室开放课题1项；参与多项国家级和省部级科研项目。

主持项目

[1] 国家自然科学基金面上项目：多源异构特征融合的可解释乳腺癌智能分级诊断辅助诊断方法研究（2024.1-2027.12，主持，No. 62371276，49万元）

[2] 国家自然科学基金青年项目：PCNN深度模型及乳腺病理图像自动分析方法研究(2016.1-2018.12，主持，No. 61501287，22万元）

[3] 中央高校基本科研业务费项目：PCNN深度模型及细胞组织图像分类检测方法研究 (2017.1-2019.12，主持)

[4] 现代教学技术教育部重点实验室开放课题：基于深度脉冲耦合神经网络的目标识别方法研究(2015.1-2016.12，主持)

[5] KIST-IRDA韩国科学技术研究院校友合作项目：Object Recognition based on SPCNN and Convolutional Deep Network Model (2015.1-2015.12，主持)

[6] 中央高校基本科研业务费项目：基于PCNN彩色图像分割的目标识别研究 (2013.1-2014.12，主持)

获奖情况

雷秀娟，谢娟英，陆铖，代才，陈昱莅. 陕西省科学技术奖(自然科学奖二等奖)，高维多尺度生物大数据模式挖掘与疾病预测．陕西省人民政府，2020年4月6日.

期刊论文

[1] Ziheng Cai, Yuli Chen*, Jinjie Wang, Xin He, Zixuan Pei, Xiujuan Lei*, Cheng Lu*. DAFNet: A novel Dynamic Adaptive Fusion Network for medical image classification. Information Fusion. 2026, vol. 126, p. 103507, 2026/02/01. （中科院SCI 一区 TOP， IF=15.5）

[2] Yuli Chen, Jiayang Bai, Jinjie Wang , Guoping Chen, Xinxin Zhang, Duan-Bo Shi, Xiujuan Lei∗ , Peng Gao∗ , Cheng Lu*. MSFusion: A multi-source hybrid feature fusion network for accurate grading of invasive breast cancer using H&E-stained histopathological images. Medical Image Analysis, 2025, 104: 103633. （中科院SCI 一区 TOP， IF=11.8）

[3] Yuli Chen, Guoping Chen, Guoying Shi, Yao Zhou, Jiayang Bai, Germán Corredor, Cheng Lu*, and Xiujuan Lei*. "SeaConvNeXt: A Lightweight Two-Branch Network Architecture for Efficient Prediction of Specific IHC Proteins and Antigens on Hematoxylin and Eosin (H&E) Images," Big Data Mining and Analytics, 2024, 7(4): 1212-1236.（中科院SCI 一区， IF=7.7）

[4] Yuli Chen, Haojia Li, Andrew Janowczyk, Paula Toro, Germán Corredor, Jon Whitney, Cheng Lu, Can F Koyuncu, Mojgan Mokhtari, Christina Buzzy, Shridar Ganesan, Michael D. Feldman, Pingfu Fu, Haley Corbin, Aparna Harbhajanka, Hannah Gilmore, Lori J Goldstein, Nancy E Davidson, Sangeeta Desai, Vani Parmar, Anant Madabhushi*. “Computational pathology improves risk stratification of a multi-gene assay for early stage ER+ breast cancer,” NPJ Breast Cancer, 2023, 9(1): 438. (Nature子刊，JCR一区， IF=7.519)

[5] Yuli Chen*, Yuhang Jia, Xinxin Zhang, Jiayang Bai, Xue Li, Miao Ma, Zengguo Sun, and Zhao Pei. "TSHVNet: Simultaneous Nuclear Instance Segmentation and Classification in Histopathological Images Based on Multiattention Mechanisms". BioMed Research International, 2022, 2022: 7921922. (中科院SCI三区， IF=3.09)

[6] Yuli Chen, Yao Zhou, Guoping Chen, Yuchuan Guo, Yanquan Lv, Miao Ma, Zhao Pei, and Zengguo Sun*. "Segmentation of Breast Tubules in H&E Images Based on a DKS-DoubleU-Net Model". BioMed Research International, 2022, 2022: 2961610.  (中科院SCI三区， IF=3.09)

[7] Zhao Pei, Yuanshuai Gou, Miao Ma, Min Guo, Chengcai Leng, Yuli Chen, Jun Li , “Alzheimer’s disease diagnosis based on long-range dependency mechanism using convolutional neural network,” Multimedia Tools and Applications, 2021. (中科院SCI 三区)

[8] Zengguo Sun, Zhihua Zhang, Yuli Chen*, Shigang Liu , and Yunjing Song, "Frost Filtering Algorithm of SAR Images With Adaptive Windowing and Adaptive Tuning Factor," IEEE Geoscience and Remote Sensing Letters, 2020, 17( 6): 1097-1101. (中科院SCI 二区)

[9] Yuli Chen, Yide Ma, Dong Hwan Kim, and Sung-Kee Park*. “Region-based Object Recognition by Color Segmentation Using a Simplified PCNN”. IEEE Transactions on Neural Networks and Learning Systems. 2015, 26 (8): 1682-1697. (中科院SCI一区，Top期刊， IF=8.9)

[10] Yuli Chen, Sung-Kee Park, Yide Ma*, and Rajeshkanna Ala. “A New Automatic Parameter Setting Method of a Simplified PCNN for Image Segmentation”. IEEE Transactions on Neural Networks, 2011, 22(6): 880-892. (中科院SCI一区，Top期刊)

会议论文

[1] Lei Ma, Jiangyue Yin, Jinhuang Nong, Meifeng Qin, Junzhe Hu, Yanbo Zhang,Yuli Chen*, Xiangchuan Li*. "PlantKnoRA:ABotanical Large Language Iodelbased on Lightweight Fine-Tuning and Tripartite Evaluation", in 2025 International Conference on Artificial Intelligence, Human-Computer Interaction and Natural Language Processing (ICAHN). DOI 10.1109/ICAHN67688.2025.00024. 2025. （EI检索）

[2] Xinxin Zhang, Cheng Lu, Jiayang Bai, and Yuli Chen*, "A multiscale attention network for grading of invasive ductal cancer," in Proc.SPIE, 2024,13208: 132081A. （EI检索）

[3] Tianyi Yang, Junqiao Xi, Jinjie Wang, Xin He, Ziheng Cai, Zixuan Pei, Yuhang Jia, Yuli Chen*. "UL-HVNet: A Lightweight Model for Multi-Scale and Multi-Frequency Feature Representation in Nuclei Multi-Instance Segmentation and Classification, " 2024 5th International Symposium on Artificial Intelligence for Medical Sciences (ISAIMS 2024), October 25-27,2024 Wuhan, China. （EI检索）

[4] Yuli Chen, Haojia Li, Andrew Janowczyk, Paula Toro, German Corredor, Cheng Lu, Shridar Ganesan, Michael D. Feldman, Pingfu Fu, Hannah Gilmore, William Barlow, Alastair Thompson, Andrew Godwin, Daniel Hayes, Kathy Albain, Anant Madabhushi*. “Computerized measurements of Nuclear Morphology Features, Mitosis Rate, and Tubule Formation from H&E Images Predicts Recurrence-Free Survival in ER+ &; LN+ Invasive Breast Cancer Patients from SWOG S8814,” in SABCS 2022. （SABCS是全球规模最大的乳腺癌学术会议）

[5] Yuli Chen, Haojia Li, Andrew R. Janowczyk, Can F. Koyuncu, Paula Toro, German Corredor, Jon Whitney, Cheng Lu, Shridar Ganesan, Michael D. Feldman, Pingfu Fu, Hannah Gilmore, Aparna Harbhajanka, Haley N. Sechrist, Sangeeta Desai, Vani Parmar, Anant Madabhushi*. “Computerized Measurements of Nuclear Morphology Features, Mitosis Rate, and Tubule Formation from H&E Images Predicts Recurrence-Free Survival in ER+ & LN- Invasive Breast Cancer: A Multi-Institutional Study,” in USCAP 110th Annual Meeting, 2021. （USCAP美国加拿大病理学会年会——全球病理学界最具影响力的国际学术盛会之一）

[6] Yuhang Jia, Cheng Lu, Xue Li, Miao Ma, Zhao Pei, Zengguo Sun, Yuli Chen*. “Nuclei Instance Segmentation and Classification in Histopathological Images using a DT-Yolact,” The 4th International Conference on Data Science and Computational Intelligence (DSCI-2021). London, UK, Dec. 20-22, 2021. (EI检索)

[7] Yuli Chen*, Xingwei Li, Huiting Yao, Xue Li, Miao Ma, Zhao Pei, Cheng Lu. “Adherent Nuclei Edge Detection Based on Caps-Unet,”. 2020 IEEE Intl Conf on Parallel & Distributed Processing with Applications, Big Data & Cloud Computing, Sustainable Computing & Communications, Social Computing & Networking (ISPA/BDCloud/SocialCom/SustainCom). Exeter, UK, Dec. 17-19, 2020. (EI检索)

[8] Yuli Chen*, Huiting Yao, Miao Ma, Zhao Pei, Xingwei Li, Zengguo Sun. “P-Spiking Deep Neural Network Based on Adaptive SPCNN Temporal Coding,”. 2019 IEEE International Conferences on Ubiquitous Computing & Communications (IUCC) and Data Science and Computational Intelligence (DSCI) and Smart Computing, Networking and Services (SmartCNS). Shenyang China, Oct. 21-23, 2019. (EI检索)

[9] Yuli Chen, Yide Ma, Dong Hwan Kim, Sung-Kee Park*. “Object Recognition based on a Simplified PCNN”. ICINCO (2), pp. 223-229, 2012. (EI检索)

授权专利

[1] 陈昱莅 贾宇航, 陆铖, 马苗, 裴炤, 李雪, 任敬, “基于自下而上路径增强的细胞实例分割方法,”专利号：ZL202011019366.5. 授权登记日：2023.12.29.

[2] 陈昱莅, 李雪, 陆铖, 马苗, 裴炤, 贾宇航, 任敬, “基于生成对抗网络和Caps-Unet网络的粘连细胞核分割方法,”专利号：ZL202010977371.0. 授权公告日：2023.07.07.

[3] 陈昱莅, 任敬, 马苗, 裴炤, 李雪, 贾宇航, “基于自注意力生成对抗网络的车牌运动模糊图像处理方法,”专利号：ZL202011557456.X. 授权公告日：2022.12.09.

[4] 陈昱莅，姚慧婷，马苗，李兴伟. “改进的脉冲深度神经网络的图像分类方法, ”专利号：ZL201810846910.X. 授权公告日：2022.05.27.

[5] 陈昱莅，周耀，陆铖,马苗,裴炤,武杰, “基于RN-DoubleU-Net网络的乳腺腺管区域图像分割方法,” 专利号：ZL 202210021366.1, 申请公布日：2022.04.29. 授权公告日：2024.04.05.

[6] 陈昱莅，陈国萍，陆铖,白佳洋, “基于Cot-cirConvNeXt网络的图像分类方法,” 专利号：ZL 202310518193.9, 申请公布日：2023.08.29. 授权公告日：2025.12.

公开专利

[1] 陈昱莅，王锦洁，蔡子恒，陆铖，石国英，裴炤, “基于MGD-DUMRN网络的图像超分辨率重建方法,” 申请号：CN 202411074980.X, 申请公布日：2024.11.22.

[2] 陈昱莅，梁凯源，张欣欣，陆铖，李岩，石国英, “基于EMA-ConvNeXt网络的图像分类方法,” 申请号：CN202410975696.3, 申请公布日：2024.11.15.

[3] 陈昱莅，蔡子恒，王锦洁，陆铖，姚超，石国英, “基于GAShuffleNet 网络的医学图像分类方法,” 申请号：CN 202410986132.X, 申请公布日：2024.11.12.

[4] 陈昱莅，张欣欣，陆铖,白佳洋,陈国萍,马苗,裴炤, “基于SN-HiFuse网络的图像分类方法,” 申请号：CN 202310746779.0, 申请公布日：2023.09.29.

[5] 陈昱莅，白佳洋，陆铖,陈国萍, “基于DC-swin-mlp网络的图像分类方法,” 申请号：CN 202310517460.0, 申请公布日：2023.07.25.

[6] 陈昱莅, 李兴伟, 马苗, 姚慧婷, “用改进的U-Net检测细胞核边缘的方法,” 申请号：CN201810734283.0, 申请公布日：2018.12.21.