个人简介
刘进，男，副教授，硕士生导师，计算机科学与工程系主任，智能影像与医工融合创新研究室负责人。2018年于东南大学获博士学位。主要从事计算机视觉，机器学习，医学图像重建及三维可视化分析等方面的研究工作。近年来先后主持或参与多项国家级和省部级项目，累计发表SCI/EI收录论文近40篇，授权专利10余项。
办公地址：安徽工程大学计算机与信息学院C507
联系邮箱：liujin@ahpu.edu.cn
代表性论文：
(1) Wang Diandian, Jin Tong, Wang Guoliang, Liu Shuai, Wang Kun, Hu Dianlin, Liu Jin*, and Liu Xilin. CASE-TCR: Content Aware and Sparse Selection Attention Driven Learning Framework for Pan-cancer Prediction Using T-Cell Receptor Sequences [J]. Knowledge-Based Systems, 2026, 341(2026): 115838. (SCI 一区)
(2) Jin Tong, Liu Jin*, Wang Diandian, Wang Kun, Miao Chenlong, Zhang Yikun, Hu Dianlin, Wu Zhan and Chen Yang. WOADNet: A Wavelet-Inspired Orientational Adaptive Dictionary Network for CT Metal Artifact Reduction [J]. IEEE Journal of Biomedical and Health Informatics, 2026, 30(2): 1452-1465. (SCI 一区)
(3) Liu Jin*, Jin Tong, Ye Zihao, Wu Fan, Wang Kun, Wu Zhan, Zhang Yikun, Hu Dianlin, and Chen Yang, LWCDNet An Interpretable Learning Weighted Convolutional Dictionary Network for Metal Artifact Reduction in CT Images [J]. IEEE Transactions on Instrumentation and Measurement, 2025, 74(2025): 4507215.
(4) Liu Jin, Wu Fan, Zhan Guorui, Wang Kun, Zhang Yikun, Hu Dianlin, and Chen Yang, DECT Sparse Reconstruction based on Hybrid Spectrum Data Generative Diffusion Model [J], Computer Methods and Programs in Biomedicine, 2025, 261(2025): 108597.
(5) Tang Shaojie, Liu Jin, Li Guo, Qiao Zhiwei, Chen Yang, and Mou Xuanqin, Statistical cone-beam CT noise reduction with multiscale decomposition and penalized weighted least squares in the projection domain [J], Journal of X-Ray Science and Technology, 2025, 33(5):959-977.
(6) 吴凡，金潼，詹郭睿，解晶晶，刘进*，张谊坤，基于多通道交叉卷积UCTransNet网络的双能CT基材料分解方法[J]. 光学学报, 2024, 44(05):0515001.
(7) Zhang TingYu, Liu Jin*, Wu Fan, Wang Kun, Subin Huang, and Zhang Yikun, Artifact suppression for sparse view CT via transformer-based generative adversarial network [J]. Biomedical Signal Processing and Control, 2024, 95(2024): 106297.
(8) Liu Jin, Kang Yanqin*, Qiang Jun, Wang Yong, Hu Dianlin, and Chen Yang, Deep residual constrained reconstruction via learned convolutional sparse coding for low-dose CT imaging [J]. Biomedical Signal Processing and Control, 2023, 85(2023): 104868.
(9) Xia Zhenyu, Liu Jin*, Kang Yanqin, Wang Yong, Hu Dianlin, and Zhang Yikun. Dynamic controllable residual generative adversarial network for low-dose computed tomography imaging [J]. Quantitative Imaging in Medicine and Surgery, 2023, 13(8):5271-5293.
(10) Liu Jin, Zhang TingYu, Kang Yanqin*, Qiang Jun, Hu Dianlin, and Zhang Yikun, SureUnet Sparse Auto-representation Encoder U-Net for Noise Artifact Suppression in Low-dose CT [J]. Neural Computing and Applications, 2023. 74(2023): 08847.
(11) Liu Jin, Kang Yanqin*, Xia Zhenyu, Qiang Jun, Zhang JunFeng, Zhang Yikun, and Chen Yang, MRCON-Net Multiscale reweighted convolutional coding neural network for low-dose CT imaging [J]. Computer Methods and Programs in Biomedicine, 2022, 221(2022): 106851.
(12) Liu Jin*, Kang Yanqin, Qiang Jun, Wang Yong, Hu Dianlin, and Chen Yang. Low-Dose CT Imaging via Cascaded ResUnet with Spectrum Loss [J]. Methods, 2022. 202(2022): 78-87.
(13) Hu Dianlin, Zhang Yikun, Liu Jin, Luo Shouhua, Chen Yang*. DIOR: Deep Iterative Optimization-based Residual learning for Limited-angle CT Reconstruction [J]. IEEE Transactions on Medical Imaging, 2022, 41(7): 1778-1790.
授权发明专利：
(1) 刘进; 吴凡; 孙宇; 晏宇豪; 刘涛; 等; 一种基于深度卷积稀疏表示重建网络的能谱CT成像方法, 2025-11-14, 中国, ZL 202310457004.1
(2) 刘进; 强俊; 刘涛; 吴凡; 孙宇; 晏宇豪; 等; 一种基于残差域迭代优化网络的低剂量CT重建方法, 2025-09-02, 中国, ZL 202210765963.5
(3) 刘进; 吴凡; 孙宇; 晏宇豪; 刘涛; 等; 基于结构增强与伪影估计的稀疏角度CT图像伪影抑制方法, 2025-08-19, 中国, ZL 202310210797.7
(4) 刘进; 王勇; 汪军; 王族; 等; 一种联合运动估计与时空张量增强表示的4D-CBCT重建方法, 2023-06-23, 中国, ZL 202010828378.6
(5) 刘进; 吴凡; 孙宇; 晏宇豪; 刘涛; 等; 一种基于深度卷积稀疏表示重建网络的能谱CT成像方法, 2023-04-25, 中国, ZL 202310457004.1
(6) 刘进; 强俊; 王勇; 夏振宇; 等; 一种基于小波多尺度卷积特征编码的稀疏角度CT重建方法, 2022-11-08, 中国, ZL 202110331020.7
(7) 刘进; 强俊; 王勇; 张庭宇; 等; 一种基于多尺度卷积编码网络的低剂量CT图像复原方法, 2022-09-27, 中国, ZL 202110911552.8
主持的科研项目：
(1)产学研项目，医疗影像数据处理分析及健康管理系统研发，2024-09 ~2025-09
(2)产学研项目，多模态融合的心脑血管疾病检测及预测系统研发，2024-11~2026-11
(3)产学研项目，基于C语言的管网智能计算服务研发，2024-07~2025-07
(4)安徽省中青年教师培养行动项目（重点项目），任务驱动的深度能谱CT成像算法研究，2023-09~2026-09
(5)安徽省高等学校科学研究项目（重点项目），卷积稀疏编码网络引导的低剂量CT图像重建方法研究，2022-09~2025-09
(6)安徽高校协同创新项目，医疗机器人研发-图像处理及相关算法研究，2019-11~2021-11
(7)计算机网络和信息集成教育部重点实验室开放基金，深度低剂量CBCT优质成像算法研究，2019-5~2021-5
(8)国家自然科学基金项目，多特征学习的肺部4D-CBCT优质重建研究，2019-01~2021-12
学生培养及荣誉：
两名学生读博深造（985、211院校），两名学生荣获研究生国家奖学金，平均每位学生发表SCI论文两篇
招生slogan：欢迎优秀的学生加入！