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学术论文

·           发表论文

[1]       Ying Wang, Dacheng Tao, Xinbo Gao, et al. Mammographic mass segmentation: em[ant]bedding multiple features in vector-valued level set in ambiguous regions. Pattern Recognition, 44(9): 1903-1915, 2011.

[2]       Xinbo Gao, Ying Wang, Xuelong Li, Dacheng Tao. On combining morphological component analysis and concentric morphology model for mammographic mass detection. IEEE Trans. on Information Technology in Biomedicine, 14(2): 266-273, 2010.

[3]       Ying Wang, Xinbo Gao. Mass detection algorithm based on support vector machine and relevance feedback. Frontiers of Electrical and Electronic Engineering in China, 3(3): 267-273, 2008.

[4]       Ying Wang, Xinbo Gao, Xuelong Li, Dacheng Tao and Bin Wang. em[ant]bedded Geometric Active Contour with Shape Constraint for Mass Segmentation. The 13th International Conference on Computer Analysis of Images and Patterns (CAIP 2009), LNCS 5702, pp.995-1002, 2009.

[5]       Ying Wang, Xinbo Gao, Jie Li. A feature analysis approach to mass detection in mammography based on RF-SVM. International Conference on Image Processing (ICIP 2007), V9-V12, 2007.

[6]       王颖, 李洁, 高新波. 基于MCA的乳腺X线图像中肿块的自适应检测方法. 电子学报, 39(3): 525-530, 2011. 

[7]       王颖, 高新波, 李洁, 王秀美. 基于PSVM的主动学习肿块检测模型. 计算机研究与发展. 49(3): 572-578, 2012.

[8]       Xinsheng Zhang, Xinbo Gao, Ying Wang. Microcalcification clusters detection with Twin Support Tensor Machines. Journal of Information & Computational Science, 5(3): 1305-1314, 2008. 

[9]    Xinsheng Zhang, Xinbo Gao, Ying Wang. MCs detection with combined image features and twin support vector machines. Journal of Computer, 4(3): 215-221, 2009.

[10]    Xinsheng Zhang, Xinbo Gao, Ying Wang. Twin support tensor machines for MCs detection. Journal of Electronics (China), 26(3): 318-325, 2009.

[11]    张新生, 高新波, 王颖, 张士杰. 乳腺X线图像的增强与噪声抑制研究. 红外与毫米波学报, 29(1): 27-31, 2010.

·           授权专利

[1]    基于机器学习的微钙化簇检测方法,授权号:ZL200910218962.3

[2]    基于非下采样Directionlet变换和压缩感知的乳腺X线图像增强方法,授权号:ZL201110098272.6

[3]  基于高分辨率字典的稀疏表征图像超分辨率重建方法,授权号:ZL201110058174.X。

[4]  基于改进视觉注意力模型的自然场景目标检测方法,授权号:ZL201010537951.4。

[5]  全天空极光图像占空比参数的提取方法,授权号:ZL201110047076.6。

·           软件著作权

[1]    医学影像处理与分析系统 MIPS V1.0,登记号:2007SR19270

[2]    医学影像信息平台 MedInfo V1.0,登记号:2009SR050555