基本信息
胡庆茂  男  博导  中国科学院深圳先进技术研究院
电子邮件: qm.hu@siat.ac.cn
通信地址: 深圳院
邮政编码: 518055

研究领域

重大疾病的智能诊疗、医学图像分析、模式识别

招生信息

   
招生专业
081104-模式识别与智能系统
083100-生物医学工程
081203-计算机应用技术
招生方向
计算机视觉
生物医学图像处理
模式识别

教育背景

1987-01--1990-08   华中科技大学   工业自动化专业博士生
1984-09--1986-12   哈尔滨工业大学   自动控制理论与应用专业硕士生
1980-09--1984-08   湖南大学   电测仪表专业本科生
学历
华中科技大学 -- 研究生
学位
华中科技大学 -- 博士

工作经历

   
工作简历
2007-03~现在,  中国科学院深圳先进技术研究院 , 医学图像与数字手术研究室 研究员 主任
2002-04~2007-03,新加坡国立科学院生物医学图像研究所, 研究员,高级研究员
2000-04~2002-03,新加坡国立科学院生物医学图像研究所, 副研究员
1997-10~2000-03,瑞士伯尔尼大学, 米勒生物力学研究所博士后,助理研究员
1996-06~1997-09,伯尔尼大学, 血管科客座科学家
1993-01~1996-05,南方医科大学, 生物医学工程系医学图像研究室副教授
1990-09~1992-12,南方医科大学, 生物医学工程系医学图像研究室讲师
社会兼职
2013-11-01-今,集成技术杂志, 执行主编

教授课程

数字图像处理
模式识别

专利与奖励

   
奖励信息
(1) 北美放射学会三等奖2006, 三等奖, 其他, 2006
(2) 北美放射学会三等奖2005, 三等奖, 其他, 2005
(3) 美国神经放射学会一等奖2005, 一等奖, 其他, 2005
(4) 北美放射学会三等奖2003, 三等奖, 其他, 2003
(5) 全军科技进步二等奖1995, 二等奖, 部委级, 1995
(6) 全军科技进步二等奖1993, 二等奖, 部委级, 1993
专利成果
[1] 胡庆茂, 张伟烽, 张晓东, 袁权. 一种限制品自动识别装置及方法. CN: CN112861888A, 2021-05-28.

[2] 胡庆茂, 苏李一磊. 图像数据增强网络的训练方法及其训练装置、介质和设备. CN: CN112164008A, 2021-01-01.

[3] 张晓东, 张轶群, 胡庆茂. 分割磁敏感加权图像中静脉血管的方法、装置和计算设备. CN: CN110634119A, 2019-12-31.

[4] 李佳颖, 胡庆茂, 张晓东. 一种软骨图像分割方法、装置、可读存储介质及终端设备. CN: CN110598714A, 2019-12-20.

[5] 郑惠敏, 胡庆茂, 张晓东, 傅贤君, 吴刚. 肋骨图像重建系统及方法、终端及可读存储介质. CN: CN110599494A, 2019-12-20.

[6] 胡庆茂, 苏李一磊, 张晓东, 傅贤君. 一种手腕骨的分割识别方法及系统、终端及可读存储介质. CN: CN109993750A, 2019-07-09.

[7] 蒋晟, 吴剑煌, 胡庆茂, 王玲, 钟卫正. 面肌训练方法、装置及电子设备. CN: CN109659006A, 2019-04-19.

[8] 胡庆茂, 张天桥. 从OCT角膜图像分割角膜结构的方法和系统. CN: CN108269258A, 2018-07-10.

[9] 陈毅, 汪震, 胡庆茂, 王岚, 黄园. 一种超声治疗系统. CN: CN108245791A, 2018-07-06.

[10] 张晓东, 胡庆茂. 弥散加权成像图像中脑缺血区域的分割方法及装置. CN: CN108122221A, 2018-06-05.

[11] 吴剑煌, 秦怡, 王浩宇, 胡庆茂. 造影剂扩散过程模拟装置. CN: CN104574503B, 2018-04-27.

[12] 陈毅, 汪震, 胡庆茂, 王岚, 黄园. 疼痛治疗用超声推拿探头及疼痛治疗装置. CN: CN107684670A, 2018-02-13.

[13] 陈毅, 汪震, 胡庆茂, 王岚, 黄园. 超声推拿探头及疼痛治疗装置. CN: CN107684672A, 2018-02-13.

[14] 陈毅, 汪震, 胡庆茂, 王岚, 黄园. 推拿探头及推拿装置. CN: CN206334222U, 2017-07-18.

[15] 陈毅, 汪震, 胡庆茂, 王岚, 黄园. 超声推拿探头及超声推拿装置. CN: CN206334224U, 2017-07-18.

[16] 胡庆茂, 张晓东, 郑惠敏, 冯维新. 一种布料图像处理方法及系统. CN: CN106934846A, 2017-07-07.

[17] 张晓东, 胡庆茂. 数字印花方法及装置. CN: CN106778881A, 2017-05-31.

[18] 胡庆茂, 张天桥. 从光学相干断层图像获取视网膜结构的方法及其系统. CN: CN106485721A, 2017-03-08.

[19] 贾富仓, 龚本伟, 贺宝春, 胡庆茂. 一种基于三维CT图像的肝脏定位方法及装置. CN: CN106204514A, 2016-12-07.

[20] 胡庆茂, 陈明扬. 一种基于支持向量机算法的脑水肿分割方法及系统. CN: CN105809175A, 2016-07-27.

[21] 胡庆茂, 景莎莎, 李维平, 任力杰. 一种急性缺血性卒中磁共振图像分析处理方法. CN: CN105787918A, 2016-07-20.

[22] 贾富仓, 李雯, 贺宝春, 胡庆茂, 方驰华, 范应方. 一种基于CT图像的肝脏肿瘤分割方法及装置. CN: CN105574859A, 2016-05-11.

[23] 贾富仓, 肖德强, 罗火灵, 胡庆茂, 方驰华, 范应方, 杨剑. 一种穿刺规划路径纠正方法及装置. CN: CN105411679A, 2016-03-23.

[24] 胡庆茂, 陈明扬. 脑中矢状线漂移测量方法与系统. CN: CN105426808A, 2016-03-23.

[25] 胡庆茂, 郑惠敏. 基于磁共振弥散加权成像确定脑缺血特征的方法和装置. CN: CN104510470A, 2015-04-15.

[26] 胡庆茂. 基于磁共振弥散加权图像确定脑缺血特征的方法和装置. CN: CN104510469A, 2015-04-15.

[27] 肖德强, 贾富仓, 罗火灵, 周寿军, 胡庆茂. 一种神经外科手术导航的注册方法及系统. CN: CN104463832A, 2015-03-25.

[28] 胡庆茂, 吴刚. 一种X光胸片肺部分割方法和装置. CN: CN104424629A, 2015-03-18.

[29] 肖德强, 罗火灵, 贾富仓, 周寿军, 胡庆茂, 方驰华, 范应方. 基于Kinect相机的术中实时注册方法. CN: CN104287830A, 2015-01-21.

[30] 胡庆茂, 李雪晨, 周寿军. 一种X光胸片图像处理方法及系统. CN: CN104252708A, 2014-12-31.

[31] 罗火灵, 贾富仓, 胡庆茂, 于红林. 一种获取人体骨密度值的方法及系统. CN: CN103892856A, 2014-07-02.

[32] 张晓东, 胡庆茂, 罗火灵, 张远修, 贾富仓. 一种X光图像处理方法、系统及X光图像处理设备. CN: CN103903254A, 2014-07-02.

[33] 罗火灵, 贾富仓, 方驰华, 范应方, 项楠, 胡庆茂. 一种标记点配准方法、装置及外科手术导航系统. CN: CN103860268A, 2014-06-18.

[34] 胡庆茂, 高爱丽, 陈明扬, 张晓东, 罗火灵, 贾富仓. 图像配准装置及其图像配准的方法. CN: CN103793904A, 2014-05-14.

[35] 岳建辉, 赵晓丽, 潘浩波, 胡庆茂. 含BMP-2和ZsGreen1基因的表达载体及其构建方法. CN: CN103525851A, 2014-01-22.

[36] 张晓东, 贾富仓, 罗火灵, 胡庆茂. 手术导航系统及手术导航方法. CN: CN103417295A, 2013-12-04.

[37] 贾富仓, 李媛, 方驰华, 范应方, 项楠, 张晓东, 罗火灵, 胡庆茂. 一种多图谱融合方法、系统及医疗设备. CN: CN103065315A, 2013-04-24.

[38] 周寿军, 胡庆茂, 谢耀钦, 辜嘉. 脑部磁共振血管造影数据的分割方法及装置. CN: CN103049913A, 2013-04-17.

[39] 贾富仓, 黄成, 罗火灵, 张晓东, 方驰华, 范应方, 胡庆茂. 一种CT图像肝脏分割的处理方法及系统. CN: CN103020969A, 2013-04-03.

[40] 胡庆茂. 自适应图像处理方法及系统. CN: CN102855617A, 2013-01-02.

[41] 周寿军, 胡庆茂, 吴剑煌, 贾富仓. 血管的建模方法. CN: CN102521873A, 2012-06-27.

[42] 胡庆茂. CT图像的处理方法及系统. CN: CN101916443A, 2010-12-15.

[43] 胡庆茂. 获取脑部特征参数的方法、系统及溶栓指征生成系统与方法. CN: CN101596109A, 2009-12-09.

[44] 胡庆茂. 一种获取脑部特征参数的方法、系统及溶栓决策系统及方法. CN: CN101332088A, 2008-12-31.

[45] 胡庆茂. 一种关于CT脑出血图像的处理方法. CN: CN101238987A, 2008-08-13.

出版信息

   
发表论文
[1] Jinping Xu, Jinhuan Zhang, Jiaying Li, Haoyu Wang, Jianxiang Chen, Hanqing Lyu, Qingmao Hu. Structural and Functional Trajectories of Middle Temporal Gyrus Sub-Regions During Life Span: A Potential Biomarker of Brain Development and Aging. Frontiers in Aging Neuroscience[J]. 2022, 14: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9094684/.
[2] Luo, Huoling, Wang, Congcong, Duan, Xingguang, Liu, Hao, Wang, Ping, Hu, Qingmao, Jia, Fucang. Unsupervised learning of depth estimation from imperfect rectified stereo laparoscopic images. COMPUTERS IN BIOLOGY AND MEDICINE[J]. 2022, 140: http://dx.doi.org/10.1016/j.compbiomed.2021.105109.
[3] Xu, Jinping, Guo, Yuanyuan, Li, Jiaying, Lv, Xinyi, Zhang, Juanjuan, Zhang, Jinhuan, Hu, Qingmao, Wang, Kai, Tian, Yanghua. Progressive cortical and sub-cortical alterations in patients with anti-N-methyl-d-aspartate receptor encephalitis. JOURNAL OF NEUROLOGY[J]. 2022, 269(1): 389-398, [4] Xu, Jinping, Wang, Jianjun, Lyu, Hanqing, Pu, Xuejia, Xu, Ziyun, Hu, Yuanming, Guo, Zhouke, Yu, Haibo, Hu, Qingmao. Different patterns of functional and structural alterations of hippocampal sub-regions in subcortical vascular mild cognitive impairment with and without depression symptoms. BRAIN IMAGING AND BEHAVIOR[J]. 2021, 15(3): 1211-1221, http://dx.doi.org/10.1007/s11682-020-00321-7.
[5] Su, Liyilei, Fu, Xianjun, Hu, Qingmao. Generative adversarial network based data augmentation and gender-last training strategy with application to bone age assessment. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE[J]. 2021, 212: http://dx.doi.org/10.1016/j.cmpb.2021.106456.
[6] Zhang, Jinhuan, Liu, Yongfeng, Lan, Kai, Huang, Xingxian, He, Yuhai, Yang, Fuxia, Li, Jiaying, Hu, Qingmao, Xu, Jinping, Yu, Haibo. Gray Matter Atrophy in Amnestic Mild Cognitive Impairment: A Voxel-Based Meta-Analysis. FRONTIERS IN AGING NEUROSCIENCEnull. 2021, 13: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044397/.
[7] Zhang, Jinhuan, Zhang, Yangxin, Hu, Liyu, Huang, Xingxian, Liu, Yongfeng, Li, Jiaying, Hu, Qingmao, Xu, Jinping, Yu, Haibo. Global Trends and Performances of Magnetic Resonance Imaging Studies on Acupuncture: A Bibliometric Analysis. FRONTIERS IN NEUROSCIENCE[J]. 2021, 14: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7854454/.
[8] Xu, Ziyun, Wang, Jianjun, Lyu, Hanqing, Wang, Runshi, Hu, Yuanming, Guo, Zhouke, Xu, Jinping, Hu, Qingmao. Alterations of White Matter Microstructure in Subcortical Vascular Mild Cognitive Impairment with and without Depressive Symptoms. JOURNAL OF ALZHEIMERS DISEASE[J]. 2020, 73(4): 1565-1573, https://www.webofscience.com/wos/woscc/full-record/WOS:000516569400025.
[9] Luo, Huoling, Yin, Dalong, Zhang, Shugeng, Xiao, Deqiang, He, Baochun, Meng, Fanzheng, Zhang, Yanfang, Cai, Wei, He, Shenghao, Zhang, Wenyu, Hu, Qingmao, Guo, Hongrui, Liang, Shuhang, Zhou, Shuo, Liu, Shuxun, Sun, Linmao, Guo, Xiao, Fang, Chihua, Liu, Lianxin, Jia, Fucang. Augmented reality navigation for liver resection with a stereoscopic laparoscope. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE[J]. 2020, 187: http://dx.doi.org/10.1016/j.cmpb.2019.105099.
[10] Xu, Jinping, Wang, Chao, Xu, Ziyun, Li, Tian, Chen, Fangfang, Chen, Kai, Gao, Jingjing, Wang, Jiaojian, Hu, Qingmao. Specific Functional Connectivity Patterns of Middle Temporal Gyrus Subregions in Children and Adults with Autism Spectrum Disorder. AUTISM RESEARCH[J]. 2020, 13(3): 410-422, https://www.webofscience.com/wos/woscc/full-record/WOS:000496512400001.
[11] Elazab, Ahmed, Wang, Changmiao, Gardezi, Syed Jamal Safdar, Bai, Hongmin, Hu, Qingmao, Wang, Tianfu, Chang, Chunqi, Lei, Baiying. GP-GAN: Brain tumor growth prediction using stacked 3D generative adversarial networks from longitudinal MR Images. NEURAL NETWORKS[J]. 2020, 132: 321-332, http://dx.doi.org/10.1016/j.neunet.2020.09.004.
[12] Xu, Jinping, Wei, Qiang, Bai, Tongjian, Wang, Lijie, Li, Xuemei, He, Zhengyu, Wu, Jianhuang, Hu, Qingmao, Yang, Xun, Wang, Chao, Tian, Yanghua, Wang, Jiaojian, Wang, Kai. Electroconvulsive therapy modulates functional interactions between submodules of the emotion regulation network in major depressive disorder. TRANSLATIONAL PSYCHIATRY[J]. 2020, 10(1): http://dx.doi.org/10.1038/s41398-020-00961-9.
[13] 魏建华, 李佳颖, 黄成健, 胡庆茂. 用于图像分割的强制召回特征注意力网络. 集成技术. 2020, 9(6): 59-70, http://lib.cqvip.com/Qikan/Article/Detail?id=7103996798.
[14] Gao, Jingjing, Zeng, Min, Dai, Xin, Yang, Xun, Yu, Haibo, Chen, Kai, Hu, Qingmao, Xu, Jinping, Cheng, Bochao, Wang, Jiaojian. Functional Segregation of the Middle Temporal Visual Motion Area Revealed With Coactivation-Based Parcellation. FRONTIERS IN NEUROSCIENCE[J]. 2020, 14: https://doaj.org/article/3f01f1040ea147de8f46c80c30f9468d.
[15] Xu, Jinping, Wang, Jiaojian, Bai, Tongjian, Zhang, Xiaodong, Li, Tian, Hu, Qingmao, Li, Hongming, Zhang, Li. Electroconvulsive Therapy Induces Cortical Morphological Alterations in Major Depressive Disorder Revealed with Surface-Based Morphometry Analysis. INTERNATIONAL JOURNAL OF NEURAL SYSTEMS[J]. 2019, 29(7): [16] Zhang, Xiaodong, Zhang, Yiqun, Hu, Qingmao. Deep learning based vein segmentation from susceptibility-weighted images. COMPUTING[J]. 2019, 101(6): 637-652, http://dx.doi.org/10.1007/s00607-018-0677-7.
[17] Zhou, Zhifeng, Xu, Jinping, Shi, Leilei, Liu, Xia, Hou, Fen, Zhou, Jingyi, Luo, Jinpei, Hu, Qingmao, Li, Hengguo. Alterations of the Brain Microstructure and Corresponding Functional Connectivity in Early-Blind Adolescents. NEURAL PLASTICITY[J]. 2019, 2019: https://doaj.org/article/859a7f5e57224392a54785d609a4bf16.
[18] Xu, Jinping, Lyu, Hanqing, Li, Tian, Xu, Ziyun, Fu, Xianjun, Jia, Fucang, Wang, Jiaojian, Hu, Qingmao. Delineating functional segregations of the human middle temporal gyrus with resting-state functional connectivity and coactivation patterns. HUMAN BRAIN MAPPING[J]. 2019, 40(18): 5159-5171, https://www.webofscience.com/wos/woscc/full-record/WOS:000482254700001.
[19] Ahmed Elazab, Ahmed M Anter, Hongmin Bai, Qingmao Hu, Zakir Hussain, Dong Ni, Tianfu Wang, Baiying Lei. An optimized generic cerebral tumor growth modeling framework by coupling biomechanical and diffusive models with treatment effects. Applied Soft Computing Journal. 2019, 80: 617-627, http://dx.doi.org/10.1016/j.asoc.2019.04.034.
[20] Li, Tian, Liu, Chunyan, Lyu, Hanging, Xu, Zhexue, Hu, Qingmao, Xu, Bibo, Wang, Yuping, Xu, Jinping. Alterations of Sub-cortical Gray Matter Volume and Their Associations With Disease Duration in Patients With Restless Legs Syndrome. FRONTIERS IN NEUROLOGY[J]. 2018, 9: https://doaj.org/article/2f599cc07d89449398d2b1d56423101a.
[21] Zhang, Xiaodong, Jing, Shasha, Gao, Peiyi, Xue, Jing, Su, Lu, Li, Weiping, Ren, Lijie, Hu, Qingmao. Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging (vol 2016, 2581676, 2016). COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINEnull. 2018, 2018: https://www.webofscience.com/wos/woscc/full-record/WOS:000450782700001.
[22] He, Baochun, Xiao, Deqiang, Hu, Qingmao, Jia, Fucang. Automatic Magnetic Resonance Image Prostate Segmentation Based on Adaptive Feature Learning Probability Boosting Tree Initialization and CNN-ASM Refinement. IEEE ACCESS[J]. 2018, 6: 2005-2015, http://ir.siat.ac.cn:8080/handle/172644/14196.
[23] Su, Liyilei, Fu, Xianjun, Zhang, Xiaodong, Cheng, Xiaoguang, Ma, Yimin, Gan, Yungen, Hu, Qingmao. Delineation of Carpal Bones From Hand X-Ray Images Through Prior Model, and Integration of Region-Based and Boundary-Based Segmentations. IEEE ACCESS[J]. 2018, 6: 19993-20008, http://ir.siat.ac.cn:8080/handle/172644/14200.
[24] Wang, Changmiao, Elazab, Ahmed, Jia, Fucang, Wu, Jianhuang, Hu, Qingmao. Automated chest screening based on a hybrid model of transfer learning and convolutional sparse denoising autoencoder. BIOMEDICAL ENGINEERING ONLINE[J]. 2018, 17(1): http://ir.siat.ac.cn:8080/handle/172644/14201.
[25] Xu, Jinping, Wang, Hongwei, Zhang, Lu, Xu, Ziyun, Li, Tian, Zhou, Zhifeng, Zhou, Zhenhui, Gan, Yungen, Hu, Qingmao. Both Hypo-Connectivity and Hyper-Connectivity of the Insular Subregions Associated With Severity in Children With Autism Spectrum Disorders. FRONTIERS IN NEUROSCIENCE[J]. 2018, 12: http://ir.siat.ac.cn:8080/handle/172644/14198.
[26] Wu, Huawang, Sun, Hui, Wang, Chao, Yu, Lin, Li, Yilan, Peng, Hongjun, Lu, Xiaobing, Hu, Qingmao, Ning, Yuping, Jiang, Tianzi, Xu, Jinping, Wang, Jiaojian. Abnormalities in the structural covariance of emotion regulation networks in major depressive disorder. JOURNAL OF PSYCHIATRIC RESEARCH[J]. 2017, 84: 237-242, http://dx.doi.org/10.1016/j.jpsychires.2016.10.001.
[27] Qin, Yi, Wu, Jianhuang, Hu, Qingmao, Ghista, Dhanjoo N, Wong, Kelvin K L. Computational evaluation of smoothed particle hydrodynamics for implementing blood flow modelling through CT reconstructed arteries. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY[J]. 2017, 25(2): 213-232, https://www.webofscience.com/wos/woscc/full-record/WOS:000398723200004.
[28] Xiao, Deqiang, Li, Yong, Luo, Huoling, Zhang, Yanfang, Guo, Xuejun, Zheng, Huimin, Hu, Qingmao, Jia, Fucang. In vivo comparison of two navigation systems for abdominal percutaneous needle intervention. ABDOMINAL RADIOLOGY[J]. 2017, 42(7): 1993-2000, http://www.chinair.org.cn/handle/1471x/1747414.
[29] Wang, Changmiao, Elazab, Ahmed, Wu, Jianhuang, Hu, Qingmao. Lung nodule classification using deep feature fusion in chest radiography. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS[J]. 2017, 57: 10-18, http://dx.doi.org/10.1016/j.compmedimag.2016.11.004.
[30] Dong, Jing, Jia, Yading, Zhang, Yaqin, Zhang, Haining, Jia, Zhijie, Zhang, Suhua, Wu, Qiang, Hu, Qingmao, Zhang, Tianqiao, Wang, Xiaogang. Anterior lens capsule and epithelium thickness measurements using spectral-domain optical coherence tomography. BMC OPHTHALMOLOGY[J]. 2017, 17(1): http://dx.doi.org/10.1186/s12886-017-0489-0.
[31] Xu, Jinping, Li, Hong, Li, Chong, Yao, JenChih, Hu, Jun, Wang, Jian, Hu, Qingmao, Zhang, Yuanchao, Zhang, Jiuquan. Abnormal cortical-basal ganglia network in amyotrophic lateral sclerosis: A voxel-wise network efficiency analysis. BEHAVIOURAL BRAIN RESEARCH[J]. 2017, 333: 123-128, http://dx.doi.org/10.1016/j.bbr.2017.06.050.
[32] Zhang, Tianqiao, Elazab, Ahmed, Wang, Xiaogang, Jia, Fucang, Wu, Jianhuang, Li, Guanglin, Hu, Qingmao. A Novel Technique for Robust and Fast Segmentation of Corneal Layer Interfaces Based on Spectral-Domain Optical Coherence Tomography Imaging. IEEE ACCESS[J]. 2017, 5: 10352-10363, http://www.chinair.org.cn/handle/1471x/1747415.
[33] Elazab, Ahmed, AbdulAzeem, Yousry M, Wu, Shiqian, Hu, Qingmao. Robust kernelized local information fuzzy C-means clustering for brain magnetic resonance image segmentation. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY[J]. 2016, 24(3): 489-507, https://www.webofscience.com/wos/woscc/full-record/WOS:000379198100013.
[34] Chen Mingyang, Zhu Shicai, Jia Fucang, Li Xiaodong, Ahmed Elazab, Hu Qingmao. Segmentation of Cerebral Edema Around Intracranial Hemorrhage on CT Scans Through Classifi cation Model Learned from Patients with both CT and T2-Weighted Magnetic Resonance Images. Journal of Integration Technology[J]. 2016, 5(5): 11-29, [35] Peiyi Gao, Jing Xue, Lu Su, Qingmao Hu, Xiaodong Zhang, Shasha Jing, Weiping Li, Lijie Ren. Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging. Hindawi Publishing Corporation. 2016, http://oa.las.ac.cn/oainone/service/browseall/read1?ptype=JA&workid=JA201902226623253ZK.
[36] Li, Xuechen, Luo, Suhuai, Hu, Qingmao, Li, Jiaming, Wang, Dadong, Chiong, Fabian. Automatic Lung Field Segmentation in X-ray Radiographs Using Statistical Shape and Appearance Models. JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS[J]. 2016, 6(2): 338-348, https://www.webofscience.com/wos/woscc/full-record/WOS:000374145800007.
[37] Xiao, Deqiang, Luo, Huoling, Jia, Fucang, Zhang, Yanfang, Li, Yong, Guo, Xuejun, Cai, Wei, Fang, Chihua, Fan, Yingfang, Zheng, Huimin, Hu, Qingmao. A Kinect (TM) camera based navigation system for percutaneous abdominal puncture. PHYSICS IN MEDICINE AND BIOLOGY[J]. 2016, 61(15): 5687-5705, http://www.corc.org.cn/handle/1471x/2375802.
[38] Xu, Jinping, Zhang, Jiuquan, Wang, Jiaojian, Li, Guanglin, Hu, Qingmao, Zhang, Yuanchao. Abnormal fronto-striatal functional connectivity in Parkinson's disease. NEUROSCIENCE LETTERS[J]. 2016, 613: 66-71, http://dx.doi.org/10.1016/j.neulet.2015.12.041.
[39] He, Baochun, Huang, Cheng, Sharp, Gregory, Zhou, Shoujun, Hu, Qingmao, Fang, Chihua, Fan, Yingfang, Jia, Fucang. Fast automatic 3D liver segmentation based on a three-level AdaBoost-guided active shape model. MEDICAL PHYSICS[J]. 2016, 43(5): 2421-2434, https://www.webofscience.com/wos/woscc/full-record/WOS:000378924200042.
[40] Zhang, Xiaodong, Jing, Shasha, Gao, Peiyi, Xue, Jing, Su, Lu, Li, Weiping, Ren, Lijie, Hu, Qingmao. Segmentation of Hyperacute Cerebral Infarcts Based on Sparse Representation of Diffusion Weighted Imaging. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE[J]. 2016, 2016: https://doaj.org/article/87367c65ca93492fa710b945339e0b19.
[41] 陈明扬, 朱时才, 贾富仓, 李晓东, Ahmed, Elazab, 胡庆茂. 基于CT和磁共振T2加权图像双模态分类模型的自发性脑出血后脑水肿在CT图像上的分割(英文). 集成技术. 2016, 11-29, http://lib.cqvip.com/Qikan/Article/Detail?id=670204154.
[42] Hu, Qingmao, Xue, Jing, Gao, Peiyi, Zheng, Huimin. Mismatch between baseline diffusion-weighted images and apparent diffusion coefficient maps predicts favourable penumbra: a retrospective study. LANCETnull. 2015, 386: 37-37, https://www.webofscience.com/wos/woscc/full-record/WOS:000366016400038.
[43] Ai, Ye, Miao, Feng, Hu, Qingmao, Li, Weifeng. Multi-Feature Guided Brain Tumor Segmentation Based on Magnetic Resonance Images. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS[J]. 2015, E98D(12): 2250-2256, https://www.webofscience.com/wos/woscc/full-record/WOS:000368904200024.
[44] Chen, Mingyang, Elazab, Ahmed, Jia, Fucang, Wu, Jianhuang, Li, Guanglin, Li, Xiaodong, Hu, Qingmao. Automatic estimation of midline shift in patients with cerebral glioma based on enhanced voigt model and local symmetry. AUSTRALASIAN PHYSICAL & ENGINEERING SCIENCES IN MEDICINE[J]. 2015, 38(4): 627-641, https://www.webofscience.com/wos/woscc/full-record/WOS:000367828100012.
[45] Elazab, Ahmed, Wang, Changmiao, Jia, Fucang, Wu, Jianhuang, Li, Guanglin, Hu, Qingmao. Segmentation of Brain Tissues from Magnetic Resonance Images Using Adaptively Regularized Kernel-Based Fuzzy C-Means Clustering. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE[J]. 2015, 2015: https://doaj.org/article/4bfd9595b05c483fb2b110b8a5b3499f.
[46] Xu, Jinping, Wang, Jiaojian, Fan, Lingzhong, Li, Hai, Zhang, Wen, Hu, Qingmao, Jiang, Tianzi. Tractography-based Parcellation of the Human Middle Temporal Gyrus. SCIENTIFIC REPORTS[J]. 2015, 5: http://ir.ia.ac.cn/handle/173211/10652.
[47] Wu, Gang, Zhang, Xiaodong, Luo, Suhuai, Hu, Qingmao. Lung Segmentation Based on Customized Active Shape Model from Digital Radiography Chest Images. JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS[J]. 2015, 5(2): 184-191, https://www.webofscience.com/wos/woscc/full-record/WOS:000352531300002.
[48] Zhang, Tianqiao, Song, Zhangjun, Wang, Xiaogang, Zheng, Huimin, Jia, Fucang, Wu, Jianhuang, Jia, Fucang, Wu, Jianhuang, Li, Guanglin, Hu, Qingmao. Fast retinal layer segmentation of spectral domain optical coherence tomography images. JOURNAL OF BIOMEDICAL OPTICS[J]. 2015, 20(9): https://www.webofscience.com/wos/woscc/full-record/WOS:000365128100032.
[49] Wu, Jianhuang, Wang, Haoyu, Zhang, Peng, Ma, Xin, Hu, Qingmao. A Preliminary Real-Time and Realistic Simulation Environment for Percutaneous Coronary Intervention. BIOMED RESEARCH INTERNATIONAL[J]. 2015, 2015: https://doaj.org/article/8c867da99c0f43b99041bb62e4d6f6ed.
[50] 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. 2014, 27-37, http://lib.cqvip.com/Qikan/Article/Detail?id=48648821.
[51] Zhang, Xiaodong, Jia, Fucang, Luo, Suhuai, Liu, Guiying, Hu, Qingmao. A marker-based watershed method for X-ray image segmentation. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE[J]. 2014, 113(3): 894-903, http://dx.doi.org/10.1016/j.cmpb.2013.12.025.
[52] Chen, MingYang, Hu, QingMao, Liu, ZhenChuan, Zhou, ShouJun, Li, XiaoDong. Segmentation of Cerebral Edema Around Spontaneous Intracerebral Hemorrhage. APPLIED MATHEMATICS & INFORMATION SCIENCES[J]. 2013, 7(2): 563-570, https://www.webofscience.com/wos/woscc/full-record/WOS:000315656500020.
[53] Zhang, Yuanxiu, Chen, Mingyang, Hu, Qingmao, Huang, Wenhua. Detection and quantification of intracerebral and intraventricular hemorrhage from computed tomography images with adaptive thresholding and case-based reasoning. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY[J]. 2013, 8(6): 917-927, https://www.webofscience.com/wos/woscc/full-record/WOS:000326455900005.
[54] Wu, Jianhuang, Hu, Qingmao, Ma, Xin. Comparative study of surface modeling methods for vascular structures. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS[J]. 2013, 37(1): 4-14, http://dx.doi.org/10.1016/j.compmedimag.2013.01.002.
[55] Zhou, Shoujun, Chen, Wufan, Jia, Fucang, Hu, Qingmao, Xie, Yaoqin, Chen, Mingyang, Wu, Jianhuang. Segmentation of brain magnetic resonance angiography images based on MAP-MRF with multi-pattern neighborhood system and approximation of regularization coefficient. MEDICAL IMAGE ANALYSIS[J]. 2013, 17(8): 1220-1235, http://dx.doi.org/10.1016/j.media.2013.08.005.
[56] Yuan, Jianjun, Liu, Lipei, Hu, Qingmao. Mathematical modeling of brain glioma growth using modified reaction-diffusion equation on brain MR images. COMPUTERS IN BIOLOGY AND MEDICINE[J]. 2013, 43(12): 2007-2013, http://dx.doi.org/10.1016/j.compbiomed.2013.09.023.
[57] Li, Yonghong, Wu, Jianhuang, Li, Hongwei, Li, Degang, Du, Xiaohua, Chen, Zhijun, Jia, Fucang, Hu, Qingmao. Automatic Detection of the Existence of Subarachnoid Hemorrhage from Clinical CT Images. JOURNAL OF MEDICAL SYSTEMS[J]. 2012, 36(3): 1259-1270, https://www.webofscience.com/wos/woscc/full-record/WOS:000303826000023.
[58] Li, YongHong, Zhang, Liang, Hu, QingMao, Li, HongWei, Jia, FuCang, Wu, JianHuang. Automatic subarachnoid space segmentation and hemorrhage detection in clinical head CT scans. INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY[J]. 2012, 7(4): 507-516, https://www.webofscience.com/wos/woscc/full-record/WOS:000306219300002.
[59] 马丽, 高培毅, 胡庆茂, 林燕, 薛静, 荆利娜, 王效春, 陈志军, 王伊龙, 廖晓凌, 刘梅丽, 刘萍, 陈伟健, 蔡业峰, 招远祺. 建立基于临床和磁共振表观弥散系数的急性前循环缺血性卒中预后评估系统. 中国卒中杂志. 2011, 6(3): 192-200, http://lib.cqvip.com/Qikan/Article/Detail?id=37097220.
[60] Ma, Li, Gao, PeiYi, Hu, QingMao, Lin, Yan, Jing, LiNa, Xue, Jing, Wang, XiaoChun, Chen, ZhiJun, Wang, YiLong, Liao, XiaoLing, Liu, MeiLi, Chen, WeiJian. Prediction of Infarct Core and Salvageable Ischemic Tissue Volumes by Analyzing Apparent Diffusion Coefficient Without Intravenous Contrast Material. ACADEMIC RADIOLOGY[J]. 2010, 17(12): 1506-1517, http://dx.doi.org/10.1016/j.acra.2010.07.010.
[61] Wu, Jianhuang, Ma, Renhui, Ma, Xin, Jia, Fucang, Hu, Qingmao. Curvature-dependent surface visualization of vascular structures. COMPUTERIZED MEDICAL IMAGING AND GRAPHICS[J]. 2010, 34(8): 651-658, http://dx.doi.org/10.1016/j.compmedimag.2010.07.006.
[62] Wu, Jianhuang, Wei, Mingqiang, Li, Yonghong, Ma, Xin, Jia, Fucang, Hu, Qingmao. Scale-adaptive surface modeling of vascular structures. BIOMEDICAL ENGINEERING ONLINE[J]. 2010, 9(1): 75-75, https://doaj.org/article/25964f9eb3884961a4849974c319995b.
[63] Hu, Q, Gao, P, Ma, L, Chen, Z, Wu, J, Ma, X. Assessing the existence of ischemic penumbra through automatically analyzing baseline diffusion-weighted imaging. JOURNAL OF CEREBRAL BLOOD FLOW AND METABOLISMnull. 2009, 29: S600-S601, https://www.webofscience.com/wos/woscc/full-record/WOS:000270329900736.
[64] 杜晓华, 胡庆茂, 黄文华. 脑实质各结构的CT测量与定位. 中国临床解剖学杂志[J]. 2009, 27(1): 67-69, http://lib.cqvip.com/Qikan/Article/Detail?id=29453884.
[65] 陈志军, 胡庆茂, 刘嘉, 杜晓华. GDCM开源库用于临床DICOM数据的问题及其解决方法. 北京生物医学工程. 2009, 28(6): 610-613, http://lib.cqvip.com/Qikan/Article/Detail?id=32490355.
[66] 胡庆茂, 马丽, 高培毅. 多模式磁共振在分析缺血性卒中可挽救脑组织中的困惑与出路. 中国卒中杂志. 2009, 762-765, http://lib.cqvip.com/Qikan/Article/Detail?id=31727113.
[67] 马丽, 高培毅, 胡庆茂, 林燕, 薛静, 荆利娜, 王效春, 陈志军, 王伊龙, 廖晓凌. 表观弥散系数对确定急性缺血性卒中缺血半暗带的潜在价值. 中国卒中杂志. 2009, 730-736, http://lib.cqvip.com/Qikan/Article/Detail?id=31727106.
[68] Zhang, Ye, Hu, Qingmao, IEEE. A PCA-Based Approach to the Representation and Recognition of MR Brain Midsagittal Plane Images. 2008 30TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-8null. 2008, 3916-3919, [69] Hu Qingmao. Supervised greyscale thresholding based on transition regions. Image and Vision Computing 2008. 2008, [70] Hu, Qingmao, Luo, Suhuai, Qiao, Yu, Qian, Guoyu. Supervised grayscale thresholding based on transition regions. IMAGE AND VISION COMPUTING[J]. 2008, 26(12): 1677-1684, http://dx.doi.org/10.1016/j.imavis.2008.05.003.
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[73] Ahmed Elazab, Ahmed M Anter, Hongmin Bai, Qingmao Hu, Zakir Hussain, Dong Ni, Tianfu Wang, Baiying Lei. An optimized generic cerebral tumor growth modelling framework by coupling biomechanical and diffusive models with treatment effects. Applied Soft Computing Journal. http://dx.doi.org/10.1016/j.asoc.2019.04.034.

科研活动

   
科研项目
( 1 ) 大脑胶质瘤的多模态图像智能分析与虚拟手术关键科学问题研究, 主持, 国家级, 2013-01--2016-12
( 2 ) 基于多模影像的缺血性脑卒中诊治新技术的关键科学问题研究, 参与, 国家级, 2013-01--2017-12
( 3 ) 基于弥散加权成像自动分析的溶栓智能决策系统, 主持, 省级, 2014-12--2016-12
( 4 ) 基于磁敏感加权图像和弥散加权成像的超急性期缺血性脑卒中影像分析研究, 主持, 国家级, 2017-01--2020-12
( 5 ) 虚拟手术仿真系统研究, 主持, 省级, 2016-06--2019-06
( 6 ) 面向人机协同的机器人智能制造感知与作业理论研究, 参与, 国家级, 2018-01--2021-12
( 7 ) 血管化仿生关节多细胞精准3D打印技术与装备的开发及应用, 主持, 国家级, 2018-05--2021-04
参与会议
(1)A fully automatic image analysis system for computer assisted diagnosis of subarachnoid hemorrhage from clinical non-enhanced CT images   北美放射学会2010   Qingmao Hu, Yonghong Li, Fucang Jia, Jianhuang Wu, Xiaohua Du, Jing Gu, Zhijun Chen   2010-11-28
(2)A fully automatic image analysis system for computer assisted diagnosis of acute ischemic stroke based on magnetic resonance diffusion-weighted imaging   北美放射学会2009   Qingmao Hu, Peiyi Gao,Zhijun Chen, Li Ma,Xiaohua Du, Jianhuang Wu, Fucang Jia, Hui Chen   2009-11-29
(3)Fast and automatic delineation of intracranial hemorrhage from clinical non-enhanced CT images   北美放射学会2008   Qiangmao Hu, Wenhua Huang, Leping Chen, Guanxun Cheng, Xiaohua Du, Zhijun Chen, Yalei Bi   2008-11-30

合作情况

北京天坛医院、中国脑卒中中心,合作脑卒中智能诊疗
广州军区陆军总医院,合作大脑胶质瘤的智能诊疗
临沂人民医院,全面战略合作
清华研究生院、澳洲纽卡斯尔大学、南方医科大学,研究生联合培养

项目协作单位
天坛医院
中国脑卒中中心
美国斯坦福大学
湖南大学
华中科技大学
清华大学深圳研究生院
厦门大学
临沂人民医院
南方医科大学
安科公司

指导学生

已指导学生

杨东  硕士研究生  080903-微电子学与固体电子学  

陈明扬  博士研究生  081203-计算机应用技术  

张天桥  博士研究生  081104-模式识别与智能系统  

王昌淼  博士研究生  081104-模式识别与智能系统  

张丽  硕士研究生  081203-计算机应用技术  

高爱丽  硕士研究生  085211-计算机技术  

唐秀娟  硕士研究生  085211-计算机技术  

秦怡  硕士研究生  085211-计算机技术  

肖德强  博士研究生  081104-模式识别与智能系统  

吴刚  硕士研究生  081104-模式识别与智能系统  

彭雨晴  硕士研究生  083100-生物医学工程  

李雯  硕士研究生  085211-计算机技术  

现指导学生

张晓东  博士研究生  081104-模式识别与智能系统  

苏李一磊  博士研究生  081104-模式识别与智能系统  

罗火灵  博士研究生  081104-模式识别与智能系统  

徐锦萍  博士研究生  081104-模式识别与智能系统  

徐紫云  硕士研究生  085208-电子与通信工程  

魏建华  硕士研究生  085211-计算机技术  

伍海涛  硕士研究生  085211-计算机技术  

陈铭林  硕士研究生  085212-软件工程  

包学志  硕士研究生  085211-计算机技术  

刘旭辉  硕士研究生  085211-计算机技术