副教授、福建省高层次人才、厦门市高层次人才

研究方向：计算机视觉，医学图像处理，数字媒体技术，计算机图形学

所在系部：数字媒体技术系

邮 箱：hongqq@xmu.edu.cn

个人网页：https://cdmc.xmu.edu.cn/info/1010/1052.htm

个人简介

计算机博士 (Ph.D. in Computer Science)，人工智能研究院、健康医疗大数据国家研究院导师。曾在香港城市大学COCHE研究中心任副研究员（合作导师：沈定刚教授、张元亭教授）。担任Scientific Reports编委，以及IEEE TMI, IEEE TNNLS, MICCAI等期刊或会议审稿人。已在IEEE TMI, IEEE TNNLS, IEEE TFS, ACM MM, MICCAI等重要学术刊物及会议上发表论文70多篇（2024年高被引论文2篇），授权国家发明专利5件。主持国家自然科学基金面上项目或作为主要人员完成国家级项目5项、省部级项目4项、其他各类项目30多项。荣获福建省高层次人才、厦门市高层次人才、厦门市高层次留学人员、厦航奖教金（科研类）等奖励。

代表性科研项目

1. 国家自然科学基金面上项目，《基于CTA影像的急性冠状动脉综合征(ACS)智能诊断关键技术研究》，2025-2028，主持

2. 福建省自然科学基金面上项目，《基于扩散深度学习模型的CTA冠脉高风险斑块智能识别研究》，2024-2027，主持

3. 拓霸（厦门）电子有限公司委托项目 《面向智慧农业的传感器监控系统研发与知识图谱构建》，2024-2025，主持

4. 颐际（福建）科技有限公司委托项目 《人体中医红外功能影像智能模型和数字疗法研发》，2024-2025，主持

5. 虚拟现实技术与系统国家重点实验室开放课题， 《结构性心脏病智能诊断与手术规划关键技术研究》，2022-2024，主持

6. 厦门黑镜科技有限公司委托项目 《3D物品重建技术研发和工具开发》，2022-2024，主持

7. 国家自然科学基金委-联合基金项目-重点支持项目，《基于边云协同的区域能源互联网优化运行智能理论与关键技术》，2021-2024，主研

8. 福建省自然科学基金面上项目，《计算机辅助冠心病诊断与手术关键技术研究》，2020-2023，主持

9. 国家自然科学基金，《高稀疏表征在三维重建中的应用研究》，2019-2021，参与

10. 国家自然科学基金，《基于隐式建模方法的个性化冠状动脉几何模型重建与再塑研究》，2016-2018，主持

11. 福建省自然科学基金，《基于隐函数建模方法的个体化虚拟肝脏模型重建研究》，2015-2018，主持

12. 国家自然科学基金，《基于图结构的消化道超声内镜图像分类算法研究》，2015-2017，参与

13. 教育部留学回国人员科研启动基金，《基于隐式建模方法的个体化动脉血管壁重建研究》，2015-2017，主持

代表性论文

1. Li. Z., Li, Y., Li, Q., Wang, P., Guo, D., Lu, L., Jin, D., Hong, Q. Q.* (2024), LViT: language meets vision transformer in medical image segmentation. IEEE Transactions on Medical Imaging, vol. 43, no. 1, pp. 96-107, 2024. (中科院1区，ESI高被引论文)

2. Hong, Q. Q. *, et al. (2024), NeuFG: Neural Fuzzy Geometric Representation for 3D Reconstruction, IEEE Transactions on Fuzzy Systems. (中科院1区)

3. Li, Z., Zheng, Y., Shan, D., Yang, S., Li, Q., Wang, B., Zhang, Y., Hong, Q. Q.*, Shen, D.* (2024), ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation. IEEE Transactions on Medical Imaging. (中科院1区，ESI高被引论文)

4. Hong, Q. Q., Lin, L., Li, Z., Li, Q., Yao, J., Wu, Q.*, Liu, K.*, Tian, J. (2024), A distance transformation deep forest framework with hybrid-feature fusion for CXR image classification, IEEE Transactions on Neural Networks and Learning Systems. (中科院1区)

5. Li, Z., Zheng, Y., Luo, X., Shan, D., and Hong, Q. Q.* (2023), ScribbleVC: Scribble-supervised Medical Image Segmentation with Vision-Class Embedding. In Proceedings of the 31st ACM International Conference on Multimedia (MM ’23), October 29-November 3, 2023, Ottawa, ON, Canada. (CCF A)

6. Qiu, Y., Li, Z., Wang, Y., Dong, P., Wu, D., Yang, X., Hong, Q. Q.*, Shen, D.* (2023), CorSegRec: A Topology-Preserving Scheme for Extracting Fully-Connected Coronary Arteries from CT Angiography, MICCAI 2023, Vancouver, Canada, October 8-12, 2023. (CCF B, Oral, 最佳论文提名)

7. Zhou, R., Shu, Z., Xie, W., Yao, J.*, Hong, Q. Q.* (2024), S2CCT: Self-Supervised Collaborative CNN-Transformer for Few-shot Medical Image Segmentation. IEEE BIBM 2024. (CCF B)

8. Yang, C., Chen, J., Li, K., and Hong, Q. Q.* (2024), FFnsr: Fast and Fine Neural Surface Reconstruction, IEEE International Conference on Multimedia and Expo (ICME2024). (CCF B)

9. Lin, Q., Xie, W., Zhou, R., Cao, X., Chen, J., Yao, J.*, and Hong, Q. Q.* (2024), DPP-Net: Difficulty Perception-Processing Heterogeneous Network for Semi-supervised Medical Image Segmentation, IEEE International Conference on Multimedia and Expo (ICME2024). (CCF B)

10. Cao, X., Xie, W., Cao, X., Zhou, R., Lin, Q., Yao, J.*, and Hong, Q. Q.* (2024), ICR-Net: Semi-supervised Medical Image Segmentation Guided by Intra-sample Cross Reconstruction, IEEE International Conference on Multimedia and Expo (ICME2024). (CCF B)

11. Shan, D., Li, Z., Chen, W., Li, Q., Tian, J., Hong, Q. Q.* (2023), Coarse-to-Fine Covid-19 Segmentation via Vision-Language Alignment, IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2023). (CCF B)

12. Zhou, R., Yao, J.*, Hong, Q. Q. *, Zheng, Y., Zheng, L. (2023), DAMS-Net: Dual attention and multi-scale information fusion network for 12-lead ECG classification. Methods, 2023. (中科院3区)

13. Zhang, W., Su, S.*, Hong, Q. Q. *, Wang, B., Li, S. (2023), Long short-distance topology modelling of 3D point cloud segmentation with a graph convolution neural network. IET Comput. Vis., 1– 14, 2023. (CCF C)

14. Zhou, R., Yao, J.*, Hong, Q. Q. *, Li, X., Cao, X. (2023), Cross Attention Multi Scale CNN-Transformer Hybrid Encoder Is General Medical Image Learner. PRCV 2023. (CCF C)

15. Lin, Q., Yao, J.*, Hong, Q. Q. *, Cao, X., Zhou, R., Xie, W. (2023), LATrans-Unet: Improving CNN-Transformer with Location Adaptive for Medical Image Segmentation. PRCV 2023. (CCF C)

16. Li, Y., Zong, Y., Sun, W., Wu, Q.*, Hong, Q. Q. *(2023), A Long-Tail Relation Extraction Model Based on Dependency Path and Relation Graph Embedding, 7th APWeb-WAIM International Joint Conference on Web and Big Data, Oct 06, 2023 - Oct 08, 2023. (CCF C)

17. Cao, X., Yao, J.*, Hong, Q. Q., Zhou, R. (2023), MEA-TransUNet: A Multiple External Attention Network for Multi-Organ Segmentation. ICCAN 2023. (CCF C)

18. Li, X., Song, S., Yao, J.*, Zhang, H., Zhou, Z., and Hong, Q. Q., Efficient Collision Detection using Hybrid Medial Axis Transform and BVH for Rigid Body Simulation, Graphical Models, 2023. (CCF B)

19. Xu, F.#, Lin, L.#, Li, Z., Hong, Q. Q. *, Liu, K.*, Li, Q., Zheng, Y., Tian, J. (2022), MRDFF: A deep forest based framework for CT whole heart segmentation, Methods, 2022. (中科院3区)

20. Li, Z.#, Li, D.#, Wang, W., Hong, Q. Q*, Li, Q., Tian, J. (2022), TFCNs: A CNN-Transformer Hybrid Network for Medical Image Segmentation, The 31st International Conference on Artificial Neural Networks (ICANN2022). (CCF C)

21. Liu, K., Zhan, P., Liang, Y., Zhang, Y., Guo, H., Yao, J., Wu, Q.*, Hong, Q. Q. * (2022). The design of error-correcting output codes algorithm for the open-set recognition. Applied Intelligence, 52, pp. 7843–7869, 2022. (中科院2区)

22. Hong, Q., Lin, L., Li, Q., Jiang, Z., Fang, J., Wang, B., Liu, K. & Huang, C. (2021). A direct slicing technique for the 3D printing of implicitly represented medical models. Computers in Biology and Medicine, 135, 104534. (中科院2区)

23. Fei Xu#, Lingli Lin#, Dihan Li, Qingqi Hong*, Kunhong Liu*,Qingqiang Wu, Qingde Li, Yinhuan Zheng, Jie Tian (2021). A Multi-Resolution Deep Forest Framework with Hybrid Feature Fusion for CT Whole Heart Segmentation, IEEE BIBM 2021. (CCF B)

24. Xiang Yu, Jian Wang, Qingqi Hong*, Raja Teku, Shui-Hua Wang*, Yudong Zhang* (2022). Transfer learning for medical images analyses: A survey, Neurocomputing. (中科院2区)

25. Liu, K., Ye, X., Guo, H., Wu, Q.*, Hong, Q. Q.. The design of soft recoding-based strategies for improving error-correcting output codes. Applied Intelligence, 52, pp. 8856–8873, 2022. (中科院2区)

26. Hong, Q., Ding, Y., Lin, J., et al. Image-Based Automatic Watermeter Reading under Challenging Environments. Sensors, 2021, 21(2): 434. (SCI)

27. Gao, J., Liu, K., Wang, B., Wang, D., & Hong, Q. (2021). An improved deep forest for alleviating the data imbalance problem. Soft Computing, 25(3), 2085-2101. (CCF C)

28. Hong, Q., Li, Q., Wang, B., Tian, J., Xu, F., Liu, K., & Cheng, X. (2020). High-quality vascular modeling and modification with implicit extrusion surfaces for blood flow computations. Computer Methods and Programs in Biomedicine, 196, 105598. (中科院2区)

29. Zhang, W., Su, S., Wang, B., Hong, Q., & Sun, L. (2020). Local k-NNs pattern in Omni-Direction graph convolution neural network for 3D point clouds. Neurocomputing, 413, 487-498. (中科院2区)

30. Huang, C., Lan, Y., Xu, G., Zhai, X., Wu, J., Lin, F., Zeng, N., Hong, Q.,…, & Zhang, G. (2021). A deep segmentation network of multi-scale feature fusion based on attention mechanism for IVOCT lumen contour. IEEE/ACM Transactions on computational biology and bioinformatics, 18(1), 62-69. (CCF B)

31. Sun, M., Liu, K., Wu, Q., Hong, Q., Wang, B., & Zhang, H. (2019). A novel ECOC algorithm for multiclass microarray data classification based on data complexity analysis. Pattern Recognition, 90, 346-362. (中科院1区)

32. Wu, Q., Kuang, Y., Hong, Q., & She, Y. (2019). Frontier knowledge discovery and visualization in cancer field based on KOS and LDA. Scientometrics, 118(3), 979-1010. (中科院2区)

33. Hong Q, Li Q, Wang B, Liu K*, Qi Q, 2019. High precision implicit modeling for patient-specific coronary arteries, IEEE access. 7: 72020-72029. (中科院3区)

34. Hong, Q. Q., Q. Li, B. Wang, K. Liu, F. Lin, J. Lin, and et al. Accurate geometry modeling of vasculatures using implicit fitting with 2d radial basis functions. Computer Aided Geometric Design, 62:206–216, 2018. (CCF B)

35. Hong, Q. Q., Yan Li, Q. Li, B. Wang, J. Yao, Q. Wu, Y. She, An implicit skeleton-based method for the geometry reconstruction of vasculatures, The Visual Computer. Vol. 32, Issue 10, pp. 1251–1262, 2016. (SCI, CCF C)

36. Hong, Q. Q., Wang, B., Li, Q., Li, Y. and Wu, Q., GPU Accelerating Technique for Rendering Implicitly Represented Vasculatures, Bio-Medical Materials and Engineering, vol. 14, no 1, pp. 1351-1357, 2014. (SCI)

37. Zou, Q., Li, J., Hong, Q. Q.*, Lin, Z., Wu, Y., Shi, H., and Ju, Y., Prediction of microRNA-disease associations based on social network analysis methods, BioMed research international, vol. 2015, 2015. (SCI)

38. Wang, B., Ge, Q., Hong, Q. Q.*, Li, Y., Liu, K., and Jiang, Z., Vascular Model Editing for 3D Printing Based on Implicit Functions, In proceedings of 14th Chinese Conference on Image and Graphics Technologies, pp. 150-160, 2019.

39. Lu, S., Chen, H., Zhou, X., Wang, B., Wang, H., and Hong, Q. Q., Graph-Based Collaborative Filtering with MLP, Mathematical Problems in Engineering, vol. 2018, 2018. (SCI)

40. Liu, K.-H., Ng, V. T. Y., Liong, S.-T., and Hong, Q. Q., Microarray Data Classification Based on Computational Verb, IEEE Access, vol. 7, pp. 103310-103324, 2019. (中科院3区)

41. Li, Q., Hong, Q. Q., Qi, Q., Ma, X., Han, X., and Tian, J., Towards additive manufacturing oriented geometric modeling using implicit functions, Visual Computing for Industry, Biomedicine, and Art, vol. 1, no. 1, pp. 1-16, 2018.

42. Wu, Q., Zhang, C., Hong, Q. Q., and Chen, L., Topic evolution based on LDA and HMM and its application in stem cell research, Journal of Information Science, vol. 40, no. 5, pp. 611-620, 2014. (中科院3区)

43. Quan, Q., Qingde, L., and Hong, Q. Q., Skeleton marching: A high-performance parallel vascular geometry reconstruction technique, 2018 24th International Conference on Automation and Computing (ICAC), 2018, pp. 1-6.

44. Han, B., Zhang, Z., Xu, C., Wang, B., Hu, G., Bai, L., Hong, Q. Q., and Hancock, E. R., Deep face model compression using entropy-based filter selection, In proceedings of International Conference on Image Analysis and Processing, pp. 127-136, 2017.

45. 郑银环, 王备战, 王嘉珺, 陈凌宇, 洪清启, 深度卷积神经网络应用于人脸特征点检测研究, 计算机工程与应用, (4): 173-178, 2019.

46. Li, H., Zhao, J., Lin, D., Su, J., Wu, Q., and Hong, Q. Q.*, The Research and Application of Reservoir Identification Model Based on Smap-ED, International Journal of Multimedia and Ubiquitous Engineering, vol. 10, no. 12, pp. 255-264, 2015.

47. Hong, Q. Q. *, A skeleton-based technique for modeling implicit surfaces, In proceedings of 6th International Congress on Image and Signal Processing, pp. 686-691, Hangzhou, China, December, 2013.

48. Hong, Q. Q. and Wang, B., Segmentation of vessel images using a localized hybrid level-set method, In proceedings of 6th International Congress on Image and Signal Processing, pp. 631 – 635, Hangzhou, China, December, 2013.

49. Hong, Q. Q.*, Chen, L., Wang, B., and Wu, Q., The Extraction of Vascular Axis Based on Signed Distance Function, In proceedings of 5th International Conference on Graphic and Image Processing, Hong Kong, October, 25-27, 2013.

50. Hong, Q. Q.*, Li, Q., and Tian, J., Local Hybrid Level-set Method for MRA Image Segmentation, In proceedings of 10th IEEE International Conference on Computer and Information Technology, pp. 1397 - 1402, Braford, UK, June, 2010.

51. Hong, Q. Q.*, Li, Q., and Tian, J., Virtual Angioscopy based on implicit vasculatures, Lecture Note in Computer Science (LNCS), vol. 6785, pp. 592-603, 2011.

52. Hong, Q. Q.*, Li, Q., and Tian, J., Implicit reconstruction of vasculatures using bivariate piecewise algebraic splines, IEEE Transactions on Medical Imaging, vol. 31, no. 3, pp. 543-553, 2012. (中科院1区)

授权国家发明专利

1. 洪清启, 姚俊峰,李狄翰,李子晗, 一种基于半监督与Transformers的医学图像分割方法及系统, 授权号: ZL 2022 1 0411699.5

2. 洪清启,江子攸,方俊,许霏, 一种面向隐式表达医学模型的3D打印切片方法, 授权号: ZL 2019 1 0769823.3

3. 洪清启, 一种基于椭球拟合径向基函数的血管建模方法, 授权号: ZL 2018 1 0639049.X

4. 姚俊峰, 周荣洲, 洪清启, 基于双注意力机制的十二导联心电信号自动分类方法, 2022-10-01, 中国, 2022 1 1211126.4

5. 孙蒙新,刘昆宏,王备战,洪清启,张海英, 一种智能嘻哈音乐歌词生成的建模方法, 授权号: ZL 2019 1 0018462.9