基本信息

秦文健   中科院深圳先进技术研究院

生物医学与健康工程研究所

医疗机器人与微创手术器械研究中心

高级工程师(副研级),博士,博士生导师


ORCID: 0000-0003-2547-0394

GoogleScholar

Home at Researchgate

电子邮件: wj.qin@siat.ac.cn
通信地址: 深圳市南山区西丽学苑大道1068号
邮政编码: 518055


研究领域

1、多模态医学影像智能计算分析

2、智能计算成像

3、医学物理

招生信息

   
招生专业
083100-生物医学工程
081104-模式识别与智能系统
085400-电子信息
招生方向
多模态医学影像智能分析
智能计算成像
医学物理

工作经历

   
工作简历
2018-11~现在, 中国科学院深圳先进技术研究院, 高级工程师
2013-11~2018-11,中国科学院深圳先进技术研究院, 工程师
2012-06~2013-11,中国科学院深圳先进技术研究院, 助理工程师
社会兼职
2020-11-01-2023-11-01,广东省精准医学应用学会, 青委会副主任委员
2020-01-01-2023-12-31,广东省生物医学工程学会智能介入医学分会, 常务委员

专利与奖励

   
奖励信息
(1) 头颈部肿瘤个体化精确放射治疗模式的建立与应用, 二等奖, 省级, 2020
(2) 肺结节智能诊断系统, 其他, 2019
专利成果
( 1 ) 一种基于压缩感知理论的全息图像高分辨率重建方法及系统, 发明, 2019, 第 1 作者, 专利号: ZL201610541875.1
( 2 ) 肿瘤超声成像特征提取方法和系统, 发明, 2016, 第 1 作者, 专利号: ZL201410201896.X
( 3 ) 一种全景数字病理图像智能分析系统及方法, 发明, 2020, 第 2 作者, 专利号: CN202010237666.4
( 4 ) 一种数字病理切片全景图像自动分析方法及系统, 发明, 2015, 第 1 作者, 专利号: CN201510922049.7
( 5 ) 一种数字病理切片全景扫描系统, 发明, 2020, 第 1 作者, 专利号: CN202011440007.7
( 6 ) 一种生化检测设备, 发明, 2020, 第 2 作者, 专利号: CN202011350806.5
( 7 ) 一种复杂场景目标检测数据集构建方法及系统, 发明, 2020, 第 1 作者, 专利号: CN202011438924.1
( 8 ) 一种基于人工智能的障碍物检测方法, 发明, 2020, 第 1 作者, 专利号: CN202011307128.4
( 9 ) 一种三维知识诊断模型构建方法和系统, 发明, 2020, 第 1 作者, 专利号: CN202011015038.8

出版信息

期刊论文:

1.      Xue, Y#., Qin, W#., Luo, C., Yang, P., Jiang, Y., Tsui, T., Niu, T. (2021). Multi-Material Decomposition for Single Energy CT Using Material Sparsity Constraint. IEEE Transactions on Medical Imaging, 40(5), 1303–1318.

2.      Liu, Y., Hou, J., Zhu, Z., Liu, B., Cao, M., & Qin, W*. (2021). Assessment of breast arteries and lymph nodes by 3D MR angiography enhancement imaging: feasibility and pilot clinical results. BMC Medical Imaging, 21(1), 1–10.

3.      Tian, Y., Xue, F., Lambo, R., He, J., An, C., Xie, Y., Qin, W*. (2021). Fully-automated functional region annotation of liver via a 2.5D class-aware deep neural network with spatial adaptation. Computer Methods and Programs in Biomedicine, 200, 105818.

4.      Qin, W., Wu, Y., Li, S., Chen, Y., Yang, Y., Liu, X., Hu, Z. (2020). Automated segmentation of the left ventricle from MR cine imaging based on deep learning architecture. Biomedical Physics & Engineering Express, 6(2), 25009.

5.      He, Y#., Qin, W#., Wu, Y., Zhang, M., Yang, Y., Liu, X., Hu, Z. (2020). Automatic left ventricle segmentation from cardiac magnetic resonance images using a capsule network. Journal of X-Ray Science and Technology, (Preprint), 1–13.

6.      Diao, S., Hou, J., Yu, H., Zhao, X., Sun, Y., Lambo, R. L., Qin, W* Luo, W. (2020). Computer-Aided Pathological Diagnosis of Nasopharyngeal Carcinoma Based on Deep Learning. The American Journal of Pathology. https://doi.org/https://doi.org/10.1016/j.ajpath.2020.04.008

7.      Wen Li, Yafen Li, Wenjian Qin, Jianyang Xu, J. X. and Y. X. (2020). MRI Synthesis from Brain CT Images Based on Deep Learning Methods for MR-guided Radiotherapy. Quantitative Imaging in Medicine and Surgery. 10 (6), 1223.

8.      Yuan, Y., Qin, W., Ibragimov, B., Zhang, G., Han, B., Meng, M. Q.-H., & Xing, L. (2019). Densely Connected Neural Network With Unbalanced Discriminant and Category Sensitive Constraints for Polyp Recognition. IEEE Transactions on Automation Science and Engineering, PP, 1–10. https://doi.org/10.1109/tase.2019.2936645

9.      Yuan, Y., Qin, W., Buyyounouski, M., Ibragimov, B., Hancock, S., Han, B., & Xing, L. (2019). Prostate cancer classification with multiparametric MRI transfer learning model. Medical Physics, 46(2), 756–765. https://doi.org/10.1002/mp.13367

10.   Liang, X., Li, N., Zhang, Z., Yu, S., Qin, W., Li, Y., Xie, Y. (2019). Shading correction for volumetric CT using deep convolutional neural network and adaptive filter. Quantitative Imaging in Medicine and Surgery, 9(7), 1242.

11.   Liu, L.#, Li, K. #, Qin, W. #, Wen, T., Li, L., Wu, J., & Gu, J. (2018). Automated breast tumor detection and segmentation with a novel computational framework of whole ultrasound images. Medical & Biological Engineering & Computing, 56(2), 183–199. https://doi.org/10.1007/s11517-017-1770-3

12.   Xiao, T., Liu, L., Li, K., Qin, W., Yu, S., & Li, Z. (2018). Comparison of Transferred Deep Neural Networks in Ultrasonic Breast Masses Discrimination. BioMed Research International, 2018, 1–9. https://doi.org/10.1155/2018/4605191

13.   Liu, Y. #, Qin, W. #, Li, R., Yu, S., He, Y., & Xie, Y. (2018). Investigation on the Neural Mechanism of Hypnosis-Based Respiratory Control Using Functional MRI. Contrast Media & Molecular Imaging, 2018. https://doi.org/10.1155/2018/8182542

14.   Zhao, W., Li, D., Niu, K., Qin, W., Peng, H., & Niu, T. (2018). Robust Beam Hardening Artifacts Reduction for Computed Tomography Using Spectrum Modeling. IEEE Transactions on Computational Imaging, 5(2), 333–342.

15.   Qin, W., Wu, J., Han, F., Yuan, Y., Zhao, W., Ibragimov, B., Xing, L. (2018). Superpixel-based and boundary-sensitive convolutional neural network for automated liver segmentation. Physics in Medicine and Biology, 63(9). https://doi.org/10.1088/1361-6560/aabd19

16.   Chen, Y., Wang, L., Li, F., Du, B., Choo, K. K. R., Hassan, H., & Qin, W. (2017). Air quality data clustering using EPLS method. Information Fusion. https://doi.org/10.1016/j.inffus.2016.11.015

17.   Li, J., Liu, Y., Nie, Z., Qin, W., Pang, Z., & Wang, L. (2017). An approach to biometric verification based on human body communication in wearable devices. Sensors (Switzerland). https://doi.org/10.3390/s17010125

18.   Wen, T., Li, L., Zhu, Q., Qin, W., Gu, J., Yang, F., & Xie, Y. (2017). GPU-accelerated Kernel Regression Reconstruction for Freehand 3D Ultrasound Imaging. Ultrasonic Imaging. https://doi.org/10.1177/0161734616689464

19.   李凌;辜嘉马青山; 刘磊; 齐守良; 秦文健; 温铁祥; (2017). 一种改进的投票算法检测细胞核. 中国医学物理学杂志, 34(8), 799–805.

20.   Wen, T., Gu, J., Li, L., Qin, W., Wang, L., & Xie, Y. (2016). Nonlocal total-variation-based speckle filtering for ultrasound images. Ultrasonic Imaging, 38(4), 254–275. https://doi.org/10.1177/0161734615600676

21.   江贵平;秦文健(*);周寿军;王昌淼. (2015). 医学图像分割及其发展现状. 计算机学报, 38(6), 1222–1242.

会议论文:

1.  Qin, W., Xiao, Z., Xie, Y., & Yuan, Y. (2020). Self-Paced Learning for Automatic Prostate Segmentation on MR Images with Hierarchical Boundary Sensitive Network. 2020 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2020, 321–326.

2.  Songhui D, Luo W, Hou J, et al. Computer Aided Cancer Regions Detection of Hepatocellular Carcinoma in Whole-slide Pathological Images based on Deep Learning. In: 2019 International Conference on Medical Imaging Physics and Engineering (ICMIPE2019). Shenzhen; 2019.

3. Wen T, Liu R, Liu L, Qin W, Li L, Gu J. GPU-based volume reconstruction for freehand 3D ultrasound imaging. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS. ; 2017.

4.   Yuan Y, Meng MQ-H, Qin W, and Xing L. Liver Lesion Detection Based on Two-Stage Saliency Model with Modified Sparse Autoencoder. Med Image Comput Comput Assist Interv – MICCAI 2017 MICCAI 2017. 2017;3:577-585. doi:10.1007/978-3-319-66179-7

5. Yuan Y, Qin W, Guo X, et al. Prostate segmentation with encoder-decoder densely connected convolutional network (ed-densenet). In: Proceedings - International Symposium on Biomedical Imaging. Vol 2019-April. ; 2019.

6. Liu L, Qin W, Yang R, et al. Segmentation of breast ultrasound image using graph cuts and level set. In: IET Conference Publications. Vol 2015. ; 2015.

7. Shen P, Qin W, Yang J, et al. Segmenting multiple overlapping nuclei in H&E stained breast cancer histopathology images based on an improved watershed. In: IET Conference Publications. 2015. doi:10.1049/cp.2015.0779.

8.  Wan Z, Qin W, Song K, Wang B, Zhang D, Li L. Semi-Supervised Representation Learning for Infants Biliary Atresia Screening Using Deep CNN-Based Variational Autoencoder. In: International Conference on Mechatronics and Intelligent Robotics. Springer, Cham; 2018:1207-1212


科研活动

   
科研项目
( 1 ) 基于注意力机制对抗模型的CT-MRI跨模态肝脏肿瘤靶区勾画方法研究, 主持, 国家级, 2020-01--2022-12
( 2 ) 基于人工智能的复杂场景下多目标辅助检测技术研发, 主持, 国家级, 2020-01--2022-12
( 3 ) 电子束近距离放疗系统研发及产业化, 主持, 省级, 2020-01--2023-01
( 4 ) 多模态无创CGM技术与系统研究, 参与, 国家级, 2019-01--2022-12
( 5 ) 脑波智能分析联合实验室, 参与, 院级, 2019-06--2022-06
( 6 ) 面向宫颈癌近距离放疗实时精准导航系统关键技术研究, 参与, 国家级, 2021-01--2024-12
( 7 ) 智能化血液病理辅助诊断联合实验室, 主持, 院级, 2021-03--2024-03
( 8 ) 基于多模态图像引导的宫颈癌实时自适应近距离治疗计划系统, 主持, 部委级, 2021-04--2024-04
( 9 ) 深广高端医疗器械国家先进制造业集群公共服务技术平台, 参与, 国家级, 2020-04--2022-03
( 10 ) 基于深度学习的数字病理图像智能分析与病理分型研究, 主持, 省级, 2020-11--2023-10
参与会议
(1)基于深度学习的医学影像分割算法关键技术   广州市医学会神经外科学分会2020年学术年会   2020-12-12
(2)基于多模智能计算的诊疗技术及临床应用   中国生物技术大会   2020-11-03
(3)人工智能技术在模拟医学中的应用关键技术综述   吴阶平基金会虚拟现实和人工智能在模拟医学中的应用研讨会   2020-10-28
(4)基于卷积神经网络的肝脏全自动分割算法及应用研究   第十五届中国肿瘤微创治疗学术大会暨南方肿瘤微创介入论坛   2019-05-26
(5)Artificial Intelligence in Medical Imaging Analysis   2018年广州医师协会青年分会年会   2018-08-19
(6)Deep Learning for Radiotherapy Planning   广东省抗癌协会放疗分会青年论坛   2017-10-15

合作情况

项目合作临床医院:

山东省立医院,山东省肿瘤医院,中国医科大学附属第一医院,辽宁省肿瘤医院,中山大学附属肿瘤医院,广东省中医院,中国医科院肿瘤医院深圳医院,广州市第一人民医院,北京大学深圳医院,深圳大学附属总医院,深圳市第三人民医院,南方医科大学中西医结合医院,重庆大学附属第一医院


指导学生

现指导学生

齐恒  硕士研究生  085211-计算机技术  

张旺  硕士研究生  085400-电子信息  

赖清佩  硕士研究生  085400-电子信息  

曾伟斌  硕士研究生  085400-电子信息  

欧阳效芸  硕士研究生  085210-控制工程