General

Shoujun Zhou 

Male, doctoral supervisor

Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences


E-mail: sj.zhou@siat.ac.cn

Address: Nanshan District, Shenzhen City Xili University City, No. 1068

Postal Code: 518055



Research Areas

Medical image processing, image-guided therapy, interventional surgery robots


Admissions Information

recruit and train master and doctoral students

Scientific research

1. Participate in the award-winning project "fPAX research and application" in the domestic Pearl River Hospital, Guangzhou Military Region, Guangzhou General Hospital, Southern Hospital radiology application so far, GE and other domestic and foreign systems more stable.

2. Participate in the award-winning project "based on the sequence of cardiac function parameters quantitative measurement system" in a number of hospitals in the domestic hospital is recognized, so far in the function, stability, accuracy is still constantly improving.

3. Cardiovascular and cerebrovascular analysis, my research results to the first author in the medical image of the international top journal Medical Image Analysis published.

4. Guided the team to carry out the research and development of vascular interventional surgery robot system, and won the "silver award of global medical robot innovation design competition" in November 2019.

Papers

[1] Shibin Wu, Pin He, Shaode Yu, Shoujun Zhou, Jun Xia, and Yaoqin Xie. To Align Multimodal Lumbar Spine Images via Bending Energy Constrained Normalized Mutual Information. BioMed Research International, Vol. 2020, Article ID 5615371, 11 pages: https://doi.org/10.1155/2020/5615371.

[2] Jianpeng Qiu(#), Tianlin lv(#), Yang Chen*, Shoujun Zhou*, Liudong Xing. An improved matrix-based endovascular guidewire position simulation using fusiform ternary tree. International Journal of Medical Robotics and Computer Assisted Surgery. Sep 2020: e2137, DOI: 10.1002/rcs.2137.

[3] Tiexiang Wen, Cheng Wang, Yi Zhang, Shoujun Zhou*. A novel ultrasound probe spatial calibration method using a combined phantom and stylus. Ultrasound in Medicine & Biology. 2020, 46(8), 2079-2089.

[4] Jianjun Zhu, Jingfan Fan, Shuai Guo, Danni Ai, Hong Song, Cheng Wang, Shoujun Zhou, Jian Yang. Heuristic tree searching for pose-independent 3D/2D rigid registration of vessel structures. Physics in Medicine and Biology, Mar 2020, 65(5):055010.

[5] Jianpeng Qiu†, Libo Zhang†, Guangyu Yang, Yang Chen*, Shoujun Zhou*. An improved real-time endovascular guidewire position simulation using activity on edge network. IEEE Access, Vol. 7: 126618-126624, 2019.

[6] Na Li, Shoujun Zhou*, Zonghan Wu, Baochang Zhang, Gang Zhao*. Statistical Modeling and Knowledge-based Segmentation of Cerebral Artery based on TOF-MRA and MR-T1. Computer Methods and Programs in Biomedicine, Apr 2020, Vol. (186): 105110.

[7] Zhang Ziyang, Lin Tao, Zhou Shoujun*, Wang Yuanquan*, Gao Xuedong. GVFOM: A novel external force for active contour-based image segmentation. Information Sciences, Jan 2020, Vol. 506: (1-18).

[8] Baochang Zhang, Shuting Liu, Shoujun Zhou*, Jian Yang, Cheng Wang, Na Li, Zonghan Wu, Jun Xia*. Cerebrovascular Segmentation from TOF-MRA using Model- and Data-driven Method via Sparse Labels. Neurocomputing, Mar 2020, 380: 162-179.

[9] Shoujun Zhou, Yao Lu, Nana Li, Yuanquan Wang*. Extension of the virtual electric field model using bilateral‑like filter for active contours. Signal, Image and Video Processing, Sep 2019, Vol. 13(6): 1131-1139.

[10] Jiang GL, Jin SK*, Ou YS* and Zhou SJ. Depth Estimation of a Deformable Object via a Monocular Camera. Appl. Sci. 2019, 9, 1366; doi:10.3390/app9071366.

[11] Ken Chen, Cheng Wang, Yaoqin Xie*, Shoujun Zhou*. A GPU-based automatic approach for guide wire tracking in fluoroscopic sequences. International Journal of Pattern Recognition and Artificial Intelligence. Jul 2019, Vol. 33(8): 1954025.

[12] Xixiong Qiu, Weizong Liu, Mingdong Zhang, Hengzhou Lin, Shoujun Zhou, Yi Lei, Jun Xia*. Application of Virtual Navigation with Multimodality Image Fusion in Foramen Ovale Cannulation. Pain Medicine, Nov 2017, Vol. 18(11): 2181-2186.

[13] Hao Shen†, Cheng Wang†, Le Xie*, Shoujun Zhou*, Lixu Gu, Hongzhi Xie. A novel robotic system for vascular intervention: principles, performances, and applications. International Journal of Computer Assisted Radiology and Surgery, Apr 2019, Vol. 14(4): 671-683.

[14] Hao Shen†, Cheng Wang†, Le Xie*, Shoujun Zhou*, Lixu Gu, Hongzhi Xie. A novel remote-controlled robotic system for cerebrovascular intervention. The International Journal of Medical Robotics and Computer Assisted Surgery, 2018, 14(6): e1943.

[15] Shoujun Zhou*, Baolin Li, Yuanquan Wang*, Cheng Wang, Tiexiang Wen, Na Li. The line- and block-like structures extraction via ingenious snake. Pattern Recognition Letters, Sep 2018, 112:324-331.

[16] Pei Lu†, Jun Xia†, Zhicheng Li, Jin Xiong, Jian Yang, Shoujun Zhou*, Lei Wang, Mingyang Chen, Cheng Wang. A vessel segmentation method for multi-modality angiographic images based on multi-scale filtering and statistical models. Biomedical Engineering Online, Nov 2016, Vol. 15:120.  

[17] He BC, Huang C, Gregory CS, Sharp G, Zhou SJ, Hu QM, Fang CH, Fan YF, and Jia FC. Fast Automatic 3D Liver Segmentation Based on a Three-level AdaBoost-Guided Active Shape Model. Medical Physics, 2016, Vol. 43(5): 2421-2434. (SCI Impact Factor 2.496, JCR-2)

[18] Yang J, Fan JF, Ai DN, Zhou SJ, Tang SY and Wang YT. Brain MR image denoising for Rician noise using pre-smooth non-local means filter. Biomedical Engineering Online, 2015, 14:2, http://www. biomedical - engineering-online.com/content/14/1/2.

[19] Zhou SJ, Chen WF, JIA FC, Hu QM, Xie YQ, Chen MY, Wu JH. Segmentation of brain magnetic resonance angiography images based on MAP-MRF with multi-pattern neighborhood system and approximation of regularization coefficient. Medical Image Analysis, 2013, Vol. 17(8): 1220-1235.

[20] Yang YH, Zhou SJ, Peng S, En Q, Wu SB, and Xie YQ. Contour Propagation Using Feature-Based Deformable Registration for Lung Cancer. BioMed Research International, 2013, Vol. 2013, Article ID 701514, 8 pages. doi:10.1155/2013/701514

[21] Chen MY, Hu QM, Liu ZC, Zhou SJ, and Li XD. Segmentation of Cerebral Edema Around Spontaneous Intracerebral Hemorrhage. Applied Mathematics & Information Sciences, Mar 2013, 7(2), 563-570.

[22] Xiao DQ, Luo HL, Jia FC, Zhou SJ, Hu QM, Fang CH, Fan YF. A Kinect based automatic patient-to-image registration method for image guided percutaneous liver surgery[J]. Computers in Biology\s&\ smedicine, 2013.

[23] Tang XJ, Zhou SJ*, Hu QM. Segmentation of Coronary CT Angiography Images Based on Deformable Model with New Edge Measures, Applied Mechanics and Materials, July 2013, Vol. 333-335, 888-896.

[24] Yuanquan Wang, Wufan Chen, Shoujun Zhou, Ting Yu and Yue Zhang. MTV: modified total variation model for image noise removal. Electronics Letters, 12th May 2011, 47(10), pp: 592-594.

[25] Shoujun Zhou, Zhengbo Zhang, Jing Zhang, Yanjun Zeng, Wufan Chen. Image-guided radiotherapy toward mobile tumor. Current Medical Imaging Reviews, Feb 2011, 7: 157-166.

[26] Shoujun Zhou, Jian Yang, Yongtian Wang, Wufan Chen*. Automatic segmentation of coronary angiograms based on fuzzy inferring and probabilistic tracking. BioMedical Engineering Online, 2010. DOI:10.1186/1475-925X-9-40.

[27] Lu ZT, Feng QJ, Zhou SJ, Chen WF. Medical image elastic registration based on discontinuity adaptive Markov Random Field Model. Imaging Science Journal, Feb 2010, 58(4): 193-201.

[28] Zhou SJ, Yang J, Chen WF, Wang YT. New approach to the automatic segmentation of coronary artery in X-ray angiograms. Science in China Series F: Information Sciences, Jun 2008, 51(1): 25-39.

[29] Liu WX, Yuan KH, Zou JY, Zhou SJ, Chen WF, Jia SW, and Xiao P. Nonnegative tensor factorization for brain CT image retrieval. International Journal of Innovative Computing Information and Control. 2008, 4 (11): 2911-2917.

[30] Yang J, Wang YT, Tang SY, Zhou SJ, Liu Y, Chen WF. Multiresolution elastic registration of X-ray angiography images using thin-plate spline. IEEE Transactions on Nuclear Science, 2007, 54 (1): 152-166.

[31] Zhou SJ, Chen WF, Zhang JG, Wang YT. Inferring the structures of coronary artery trees in angiogram images using the multi-feature based fuzzy recognition algorithm. Springer-Verlag Berlin Heidelberg), Lecture Notes in Computer Science, Vol. 4091: Medical Imaging and Augmented Reality (MIAR), Berlin, 2006, 325-332.

[32]周寿军, 张吉庆. 一种新型的不变性快速图像识别方法. 甘肃工业大学学报, 2000, 26(3): 73-79

[33]李丽,刘越,王涌天,周寿军. 冠脉造影图像血管增强新方法研究,中国医学影像技术,231),pp: 129-1322007

[34]周寿军, 梁斌, 陈武凡. 心脏序列图像运动估计新方法: 基于广义模糊梯度矢量流场的形变曲线运动估计与跟踪. 计算机学报, 2003, 26(11): 1470-1479

[35]周寿军, 陈武凡. 医学图­像轮廓跟踪的广义模糊粒子滤波方法. 计算机学报, 2005, 28(1):88-96.

[36]周寿军, 陈武凡. 基于增强的粒子滤波算法的医学图像动态轮廓跟踪新方法. 第一军医大学校报, 2004, 24(6): 677-681

[37]周寿军, 梁斌,陈武凡. 一种基于模糊Gibbs随机场的运动估计新算法. 中国图像图形学报, 2004,  9(6): 699-705.

[38]周寿军, 陈武凡, 王涌天. 基于模糊识别与概率跟踪的冠状动脉造影图像血管提取. 电子学报, 2006, 34(7): 1270-1275, 2006

[39]林亚忠, 陈武凡, 杨丰, 周寿军. 基于混合金字塔吉布斯随机场的图像分割.中国生物医学工程学报, 2004, 23(1): 79-82.

[40]贾冬焱, 周寿军, 郝立巍, 李树祥. 基于相似性测度和似然模型的血管造影图像分割新方法. 光学技术., 2007, 332: 252-257

[41]贾冬焱, 周寿军, 郝立巍, 李树祥. 自动测量造影图像中血管中心线和宽度的新方法. 中国生物医学工程学报, 262: 214-219, 2007.

[42]江贵平, 周寿军. 利用模糊识别算法分析冠状动脉造影图像中的血管结构。中国计算机学报, 2008, 31(1): 170-175页,2008年。

[43]杨健王涌天唐宋元周寿军刘越. 基于互信息量和薄板样条的X射线造影图像弹性配准. 中国电子学报, 2007, 35(1): 127-130.

[44]杨健, 王涌天, 唐宋元, 周寿军, 刘越. DSA血管三维重建技术分析与展望. 中国生物医学工程学报, 2005, 24(6): 655-661.

[45]周寿军, 肖世群, 崔智, 童若锋, 杨俊. 动态放射治疗中的肿瘤实时跟踪技术. 中国生物医学工程学报, 2008, 27(5): 773-782.

[46]周寿军, 周志洋, 邱建平, 王文辉, 尹洪男. 基于后验概率的呼吸信号预测. 中国生物医学工程学报, 2009, 28(2): 213-220.

[47]杨俊, 吴庆洲, 李洪亮, 周寿军*, 尹岭. 基于投影图像和CT容积图像的三维冠状动脉运动跟踪新方法. 生物医学工程与临床, 2010, 14(4): 294-299.

[48]杨俊, 吴庆洲, , 周寿军*, 尹岭. 实时图像引导放射治疗技术研究. 生物医学工程与临床, 2010, 14(5): 458-464.

[49]郑曲波, 李洪亮, 杨媛, 吴桂良, 周寿军*. 利用圆周探测和Gabor 滤波器鉴别血管结构的新方法. 南方医科大学学报, 2010, 30(9): 2063-2069.

[50]梅川,吴桂良,杨媛,谢斓,何家驹,李绍林,周寿军*. 一种基于区域增长和结构识别的心血管X线造影图像分割方法。生物医学工程学杂志,20144月,31卷2期:413-420

[51]周辉, 杨媛,白利民,周寿军,卢振泰. 基于调幅-调频与熵图多模态医学图像的配准. 中国组织工程研究与临床康复, 2011,15(30): 5600-5603.

[52]李洪亮, 吴桂良, 刘颖,. 三维血管造影数据的分割[J]. 生物医学工程与临床, 2012, 16(01):99-104.

[53]邢磊, 陈艳, 辜嘉,. 内照射放疗机器人的研究[J]. 集成技术, 2012(02).

[54]杨俊, 郑曲波, 吴桂良, 高兴旺, 李洪亮, 周寿军*. 基于Metropolis-SA算法的脑部磁共振血管造影图像分割. 《生物医学工程与临床》,17(2): 113-118, 2013.

[55]杨俊, 周辉, 郑曲波, 吴桂良, 周寿军*. 基于高斯混合噪声和随机模型的冠脉造影数据仿真. 《系统仿真学报》,20132511):2655-2661

[56]周辉,何家驹,杨媛,向征,谢斓,李绍林,周寿军*. 一种分割冠状动脉X射线造影图像的有效方法. 《生物医学工程与临床》,201317(4): 312-315.

[57]吴庆洲,向征,何家驹,谢斓,李绍林,周寿军*. 三维人体图谱设计关键技术研究. 《生物医学工程与临床》,201317(2): ,108-112.

[58]周寿军,贾富仓,胡庆茂,谢耀钦,辜嘉,尚鹏. 基于Markov随机场的脑部三维磁共振血管造影数据的分割. 《集成技术》20143(1), 27-37.

[59]胡庆茂,李永红,贾富仓,吴剑煌,周寿军*. 蛛网膜下腔出血计算机辅助诊断的现状与展望. 集成技术》2012年第01

[60]陆培,王磊,李志成,周寿军*. 一种普适的基于多尺度滤波和统计学混合模型的血管分割方法. 中国生物医学工程学会, 中国生物医学工程学报, 2016, 35(5):519-525.

[61]江贵平, 秦文健, 周寿军,. 医学图像分割及其发展现状[J]. 计算机学报, 2015, 38(6):001222-1242.

[62]杨俊,李娜,李迟迟,周寿军*. 基于高斯混合模型和马尔科夫随机场的脑MR图像分割. 《解剖学研究》,2018405):425-429

[63]杨俊,李娜,李迟迟,周寿军*. 一种新颖的 CT 血管造影图像的血管中心线提取方法. 《国际医药卫生导报》,20182417):27~30

Patents

[1].    周寿军, 陈武凡。发明专利:基于广义模糊梯度矢量流的医学序列图像运动估计方法(ZL03140277.1),授权时间:2005/7/27

[2].    周寿军。发明专利:呼吸运动预测的方法ZL 2008 1 0142585.5;授权时间:2010/12/15

[3].    周寿军,胡庆茂,吴剑煌,贾富仓。发明专利:血管建模方法(ZL 2100 1 0374015.0.授权时间2014/3/5

[4].    周寿军、胡庆茂、谢耀钦、辜嘉。发明专利:脑部磁共振血管造影数据的分割方法及装置. 授权日期:2016-1-27;授权公告号:ZL201210575653.3

[5].    胡庆茂,李雪晨,周寿军。发明专利: 一种X光胸片图像处理方法与系统. 申请日:2013-6-28,申请号:201310269818.9

[6].    肖德强,罗火灵,贾富仓,周寿军,胡庆茂,方驰华,范应方。发明专利:一种基于Kinect相机的术中实时注册方法. 申请日: 2013-7-18,申请号:2013103029774 

[7].    吴剑煌,李艳丽,周寿军,马炘。发明专利:一种管状物体中心线的提取方法. 申请日:2012-10-12;申请号:2012103874041

[8].    肖德强,贾富仓,罗火灵,周寿军,胡庆茂。发明专利:一种神经外科手术导航的注册方法及系统。申请日2013-9-25,申请号:201310442944.X

[9].    尚鹏侯增涛周寿军。发明专利:一种便携式按摩鞋、按摩系统及按摩方法. 申请日期2013-09-27;申请号:201310450063.2

[10]. 中国发明专利,一种放射性粒子植入手术机器人,申请日期:2018.09.30,申请号:CN201811155861.1,滕皋军,郑海荣,周寿军,张毅,温铁祥,王澄。(实审)

[11]. 美国发明专利,METHOD AND APPARATUS FOR EXTRACTING CENTERLINE OF TUBULAR OBJECT ,申请日期:2018.08.13,申请号:US16/077523周寿军,李宝林,王澄,陆培。(初审)

[12]. 美国发明专利,Method, apparatus, device and storage medium for extracting a cardiovisceral vessel from a cta image,申请日期:2018.07.25,申请号:US16/044662周寿军,张保昌,李宝林,王澄,陆培。(公开)

[13]. 中国发明专利,一种放射性粒子植入手术机器人,申请日期:2018.07.23,申请号:CN201810813514.7,滕皋军,郑海荣,周寿军,张毅,温铁祥,王澄。(实审)

[14]. 中国发明专利,一种脑血管分割方法、系统及电子设备,申请日期:2018.07.06,申请号:CN201810736868.6,李娜,周寿军,李迟迟,王澄。(实审)

[15]. 中国外观专利,放射性粒子植入穿刺机器人,申请日期:2018.07.02,申请号:201830348684.3,郑海荣,滕皋军,王澄,温铁祥,周寿军,张毅。(授权)

[16]. 中国外观专利,同轴式导丝导管交替介入执行机构,申请日期:2018.05.25,申请号:201830249338.X,温铁祥,王澄,李迟迟,周寿军。(授权)

[17]. 中国外观专利,机器人执行装置,申请日期:2018.03.19,申请号:201830101023.0,李迟迟,王澄,周寿军。(授权)

[18]. 中国外观专利,血管介入机器人,申请日期:2018.02.07,申请号:201830058534.9,李迟迟,王澄,温铁祥,周寿军。(授权)

[19]. 中国发明专利,一种体模的制备方法,申请日期:2017.12.19,申请号:CN201711375106.X,王澄,李迟迟,曾泉,周寿军。(实审)

[20]. 中国外观专利,导丝推进装置,申请日期:2017.12.18,申请号:201730648803.2,王澄,李迟迟,曾泉,周寿军。(授权)

[21]. 中国发明专利,基于socket的异步通信方法、存储介质及处理器,申请日期:2017.12.18,申请号:CN201711366866.4,王澄,曾泉,周寿军。(实审)

[22]. 世界知识产权组织其他专利,目标轮廓提取方法、装置、设备及存储介质,申请日期:2017.12.08,申请号:PCT/CN2017/115255,李宝林,周寿军。(初审)

[23]. 中国发明专利,目标轮廓提取方法、装置、设备及存储介质,申请日期:2017.12.08,申请号:CN201711294918.1,李宝林,周寿军。(实审)

[24]. 中国发明专利,一种医学影像中的导丝追踪方法、装置、设备及存储介质,申请日期:2017.09.27,申请号:CN201710885851.2,王澄,来源,邹亚,周寿军。(实审)

[25]. 中国发明专利,骨骼CT图像的骨骼边缘提取方法、装置、设备及存储介质,申请日期:2017.09.22,申请号:CN201710863598.0,陆培,周寿军。(实审)

[26]. 中国发明专利,数字脑可视化方法、装置、计算设备及存储介质,申请日期:2017.08.18,申请号:CN201710710028.8,王澄,李迟迟,李江宁,周寿军。(实审)

[27]. 中国发明专利,脑组织结构提取方法、装置、设备及存储介质,申请日期:2017.08.18,申请号:CN201710710002.3,王澄,李江宁,李迟迟,周寿军。(实审)

[28]. 世界知识产权组织其他专利,在CTA图像中提取心血管方法、装置、设备及存储介质,申请日期:2017.07.26,申请号:PCT/CN2017/094476周寿军,张保昌,李宝林,王澄,陆培。(公开)

[29]. 中国发明专利,在CTA图像中提取心血管方法、装置、设备及存储介质,申请日期:2017.07.26,申请号:CN201710618659.7周寿军,张保昌,李宝林,王澄,陆培。(实审)

[30]. 中国发明专利,血管树提取方法、装置、设备及存储介质,申请日期:2017.06.28,申请号:CN201710508394.5周寿军,王澄,李宝林,陆培。(实审)

[31]. 世界知识产权组织其他专利,一种管状目标中心线的提取方法及装置,申请日期:2017.05.24,申请号:PCT/CN2017/085704周寿军,李宝林,王澄,陆培。(公开)

[32]. 中国发明专利,一种管状目标中心线的提取方法及装置,申请日期:2017.05.24,申请号:CN201710373385.X周寿军,李宝林,王澄,陆培。(实审)

[33]. 中国发明专利,一种血管脊线追踪方法及装置,申请日期:2016.10.11,申请号:CN201680001076.3周寿军,陆培,陈明扬,王澄。(实审)

[34]. 中国发明专利,一种基于图像梯度矢量流场的血管脊点提取方法及装置,申请日期:2016.10.11,申请号:201680001077.8周寿军,陆培,王澄,陈明扬。(授权)

[35]. 中国发明专利,一种血管管腔结构重建方法,申请日期:2016.08.19,申请号:CN201610688927.8,王澄,周寿军,许昊申,陆培,陈明扬。(实审)

[36]. 中国发明专利,一种介入手术中的导丝力学分析方法、系统及电子设备,申请日期:2019.10.10申请号:CN201910958017.0,马雅,王澄,李迟迟,周寿军,钱瀚欣。(初审)

[37]. 中国发明专利,一种基于图搜索的介入手术路径规划方法、系统及电子设备,申请日期:2019.09.10,申请号:CN201910853457.X,钱瀚欣,王澄,李迟迟,周寿军,马雅。(初审)

[38]. 世界知识产权组织其他专利,放射粒子植入穿刺机器人,申请日期:2019.08.29,申请号:PCT/CN2019/103319,滕皋军,周寿军,林晓锋,王澄,张毅,温铁祥,陆建。(初审)

[39]. 中国发明专利,放射粒子植入穿刺机器人,申请日期:2019.08.29,申请号:CN201910808516.1,滕皋军,周寿军,林晓锋,王澄,张毅,温铁祥,陆建。(初审)

[40]. 中国外观专利,门静脉粒子支架植入机构,申请日期:2019.07.16,申请号:CN201930378148.2,王澄,李迟迟,周寿军,林晓锋。(初审)

[41]. 中国发明专利,一种动静脉畸形分割方法、系统及电子设备,申请日期:2019.06.25,申请号:CN201910552911.8,吴宗翰,周寿军,张保昌,李娜,李迟迟,王澄。(初审)

[42]. 中国外观专利,导丝微导管介入机器人,申请日期:2019.05.17,申请号:201930239492.3,林晓锋,王澄,李迟迟,周寿军。(授权)

[43]. 中国发明专利,一种血管介入手术机器人和设备,申请日期:2019.05.17,申请号:CN201910411154.2,林晓锋,王澄,李迟迟,周寿军。(实审)

[44]. 中国发明专利,一种机器人,申请日期:2019.05.16,申请号:CN201910405489.3,林晓锋,王澄,李迟迟,周寿军。(实审)

[45]. 中国发明专利,追踪导丝尖端的方法、系统及存储介质,申请日期:2019.05.15,申请号:CN201910402245.X,王澄,李迟迟,周寿军。(实审)

[46]. 世界知识产权组织其他专利,基于半监督的GMM-MRF的脑血管分割方法,申请日期:2019.03.07,申请号:PCT/CN2019/077344,张保昌,周寿军,李迟迟,王澄,吴宗翰。(初审)

[47]. 中国发明专利,图像处理方法、系统、计算设备及存储介质,申请日期:2019.03.07,申请号:CN201910172383.3,张保昌,周寿军,李迟迟,王澄,吴宗翰。(实审)

 

软件著作权:

[48]. 王澄,许昊申,周寿军.软件著作权名称:基于医学影像的血管可视化评估平台。登记号:2016SR206140  登记日:2016-06-12

[49]. 王澄,杜月,周寿军软件著作权名称:基于曲面重建技术的医学影像分析软件 V1.0 登记号:2016SR254877  登记日:2016-07-15

[50]. 王澄,邹亚,周寿军,来源:x射线影像实时分析与可视化平台。登记2017/07/14;登记号:2017SR372946

[51]. 王澄,曾泉,周寿军:远程操作推进机构软件。登记日期:2017/07/18;登记号:2017SR377493

[52]. 王澄,迟迟,周寿军:多种医学影像的可视化及分析软件。登记日期:2017/07/18;登记号:2017SR377482


Research Interests

Medical image processing, computer aided diagnosis, interventional surgery robot

Conferences

[64] Jianpeng Qiu#, Jian Yang#, Libo Zhang, Guanyu Yang, Yang Chen*, Shoujun Zhou*, Jian Zhu, Baosheng Li. An improved real-time endovascular guidewire position simulation. In Proceedings of the 2020 International Conference on Science, Health and Medicine (ICSHM-2020).

[65] Na Li, Jun Yang, Shoujun Zhou, Zonghan Wu and Baochang Zhang. "Automatic arteriovenous separation of brain via TOF-MRA and MR-T1." In International Conference on Medical Imaging Physics and Engineering (ICMIPE), 2019.

[66] Xiaofeng Lin, Hanxin Qian, Shoujun Zhou, et al., "Towards Rebuild The Interventionist's Intra-Operative Natural Behavior: A Fully Sensorized Endovascular Robotic System Design." International Conference on Medical Imaging Physics and Engineering (ICMIPE). 2019

[67] Yi Lin, Tiexiang Wen, Shoujun Zhou, Cheng Wang, Chichi Li. "One-Class Artificial Neural Network Based Liver Vessel Segmentation" In International Conference on Medical Imaging Physics and Engineering (ICMIPE), 2019.

[68] Baochang Zhang, Chichi Li, Zhimeng Xue, Shoujun Zhou* and Gang Zhao*. Locating Cerebral Arteriovenous Malformation from TOF-MRA Images using Weighted Cross-plane Dilated Convolution. 13th IEEE-EMBS International Summer School and Symposium on Medical Devices and Biosensors (MDBS’2019) in conjunction with the 11th International School and Symposium on Biomedical and Health Engineering (BHE’2019), Chengdu (China), September 28-29, 2019.

[69] Shoujun Zhou, Na Li, Baochang Zhang, Cheng Wang, Zonghan Wu, Jian Yang and Chien Aichi Chen*. Statistical Intensity- and Shape-modeling to Automate Cerebrovascular Segmentation from TOF-MRA Data. International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI2019). LNCS, volume 11765, pp. 164–172, Oct 2019, Shenzhen China.

[70] Zonghan Wu, Baochang Zhang, Jun Yang, Na Li, and Shoujun Zhou*. Segmentation of Arteriovenous Malformation Based on Weighted Breadth-first Search of Vascular Skeleton. In proceedings of 23rd Conference on Medical Image Understanding and Analysis, pp:301-309, 24-26 July 2019, Liverpool, UK.

[71] Zhang BC, Wu ZH, Liu ST, Zhou SJ*, Li N, and Zhao G. A Device-independent Novel Statistical Modeling for Cerebral TOF-MRA data Segmentation. In Proccedings of MICCAI-Workshop on Clinical Image-based Procedures, pp: 172-181, Oct 2019.

[72] Li BL and Zhou SJ*. Ingenious Snake: An Adaptive Multi-Class Contours Extraction. (Vol.1004, pp.012021). Journal of Physics: Conference Series, v 1004, n 1, April 25, 2018, 2nd International Conference on Machine Vision and Information Technology, CMVIT 2018

[73] Fan Zhang, Pei Lu, Xiaoyun Liu, Zhou SJ*. Vascular Centerline Extraction of CTA Images Based on Minimal Path and Bayesian Tracking [C]// 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2017.

[74] Yuhao Zhang, Pei Lu, Xiaoyun Liu, Zhou SJ*. A Modified MRF Segmentation of Brain MR Images [C]// 10th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics (CISP-BMEI), 2017.  

[75] Zhang D, Wang C, Zhou SJ*. A new method of vessel centerline extraction from 3D CT coronary angiography based on open-snake. IET International Conference on Biomedical Image and Signal Processing (ICBISP), Beijing, P.R. China, 2015, 11.19-11.19.

[76] Lu P, Wang C, Zhou SJ*. A vessel segmentation method for MRA data based on probabilistic mixture model. International Conference on Biomedical Image and Signal Processing (ICBISP), IET, Beijing, P.R. China, 2015, 11.19-11.19

[77] Gong Z, Shen ZX, Zhang D, Zhou SJ*. One-click detection of coronary artery ostia from three-dimensional CTA data, IEEE International Conference on Information and Automation. Lijiang, China, IEEE, 2015, 8.08-8.10, pp:877- 880

[78] Xiao DQ, Luo HL, Jia FC*, Zhou SJ, Hu QM, Fang CH, Fan YF. A novel automatic patient-to-image registration method for image guided percutaneous liver surgery. The 6th WACBE World Congress on Bioengineering. 370-371. 2013.

[79] Zhou SJ, Chen WF*, JIA FC, HU QM*, Xie YQ, Chen MY, Shang P. Segmentation of Brain Magnetic Resonance Angiography Images Based on MAP-MRF with Multi-pattern Neighborhood System. In proceedings of The IEEE International Conference on Medical Imaging Physics and Engineering (ICMIPE), pp: 135-139, 19-20 October 2013, Shenyang, China.

[80] Kui Fang, De-Feng Wang, L.M. Lui, Shou-Jun Zhou, W.C.W. Chu, A.T. Ahuja, Pheng Ann Heng. 3D model-based method for vessel segmentation in tof-MRA. Proceedings of the 2011 International Conference on Machine Learning and Cybernetics, Guilin, 10-13 July, 2011, pp: 1607-1611.

[81] Li YL, Zhou SJ, Wu JW, Ma X, Peng KW. A novel method of vessel segmentation for X-Ray coronary angiography images. The 4th International Conference on Computational and Information Sciences (ICCIS). Chongqing, China, 2012, pp: 468 – 471.

[82] Wang S, Li BN, Zhou SJ. A segmentation of coronary angiograms based on multi-scale filtering and region-growing. The 2012 International Conference on Biomedical Engineering and Biotechnology (iCBEB). Macau, China, 678-681.

[83] Zhou SJ, Yang J, Xiao SQ, Wang WH. Real-time image-guided radiation therapy: A survey. Proceedings of the 3rd International Conference on Bioinformatics and Biomedical Engineering, Beijing, China, 2009.

[84] Zhou SJ, Zhang ZB, Chen WF, Yang J. Automatic Segmentation of Coronary Angiograms Based on Probabilistic Tracking. Proceedings of the 3rd International Conference on Bioinformatics and Biomedical Engineering, Beijing, China, 2009.

[85] Yang J, Zhang ZB, Zhou SJ, Yin HN. Respiratory motion prediction based on maximum posterior probability. Proceedings of the 3rd International Conference on Bioinformatics and Biomedical Engineering, Beijing, China, 2009.

[86] Zhou SJ, Chen WF, Liang B. A new method for robust contour tracking in cardiac image sequences. IEEE International Conference ISBI, Marriott Crystal Gateway, 2004, 181-184. 

[87] Chen WF, Zhou SJ, Liang B. LV contour tracking in MRI sequences based on the generalized fuzzy GVF. IEEE International Conference on Image Processing, 2004, Singapore, 373-376.

[88] Zhou SJ, Chen WF, Wang YT. Contour tracking of left ventricle based on generalized fuzzy particle filter. IEEE International Workshop on Nonlinear Signal and Image Processing, Japan, 2005, 567-570.

Students

已指导学生

唐秀娟  硕士研究生  085211-计算机技术  

龚震寰  硕士研究生  083100-生物医学工程  

现指导学生

张保昌  硕士研究生  085211-计算机技术  

李娜  博士研究生  081104-模式识别与智能系统  

吴宗翰  硕士研究生  085211-计算机技术  

齐恒  硕士研究生  085211-计算机技术  

林晓锋  硕士研究生  081104-模式识别与智能系统