[1 ]杜秀丽,胡兴,陈波,等.基于加权非局部相似性的视频压缩 感知多假设重构算法[J].计算机科学,2019,46 ( 1): 291-296.
Du XL, Hu X, Chen B, et al. Multi-hypothesis reconstruction algorithm of DCVS based on weighted non-local similarity [ J]. Computer Science ,2019,46( 1) : 291-296.
[2 ]刘歌,芮国胜,田文飕.基于结构特征约束两阶段重构的视频 压缩感知[J].系统工程与电子技术,2020,42 ( 11 ): 2441-2449.
Liu G, Rui GS, Tian WB. Video compressed sensing based on two-phase reconstruction of structural feature prior constraints [J ]. Systems Engineering and Electronics, 2020 , 42 ( 11 ): 2441-2449.
[3 ]赵辉,杨晓军,张静,等.基于结构组全变分模型的图像压缩 感知重建[J].电子与信息学报,2020,42(11) =2773-2780.
Zhao H, Yang XJ, Zhang J, et al. Image compressed sensing reconstruction based on structural group total variation [ J ].
Journal of Electronics & Information Technology, 2020,42(11): 2773-2780.
[4 ]吴科永,陈东,辛宁,等.压缩感知和相似性约束的图像超分 辨率重构算法[J].计算机应用研究,2019,36 ( 5): 1555-1559.
Wu KY, Chen D, Xin N, et al. Compressed sensing and similarity constraint image super-resolution [ J]. Application Research of
Computers,2019,36(5) : 1555-1559.
[5 ]赵辉,方禄发,张天骐,等.基于组稀疏表示和加权全变分的 图像压缩感知重构[J].系统工程与电子技术,2020,42 (10) :2172-2180.
Zhao H, Fang LF, Zhang TQ, et al. Image compressive sensing reconstruction via group sparse representation and weighted total variation [ J ] . Systems Engineering and Electronics, 2020 , 42 (10) :2172-2180.
[6 ]马培旗,袁玉山,张宗夕,等.基于压缩感知技术三维MRI用 于半月板损伤[J].中国医学影像技术,2020,36( 10): 1533-1536.
Ma PQ, Yuan YS,Zhang ZX,et al. Three dimensional MRI based on compressed sensing technology in d這gnosis of meniscal injuries [ J ]. Chinese Journal of Medical Imaging Technology, 2020,36(10) : 1533-1536.
[7]魏敏,王松,吴亚东.医学图像可视化的视觉优化方法[J].计 算机辅助设计与图形学学报,2019,31(4):659-667.
Wei M,Wang S, Wu YD. Research on visual optimization method of medical image visualization [ J ]. Journal of Computer-Aided Design & Computer Graphics,2019,31(4) :659-667.
[8 ]李碧草,李润川,刘洲峰,等.基于非扩展嫡相似度的三维医 学图像配准[J].计算机应用与软件,2020,37(11) =95-100.
Li BC, Li RC, Liu ZF, et al. Three-dimensional medical image registration based on nonextensive entropic similarity measure [J ]. Computer Applications and Software, 2020, 37 ( 11 ): 95-100.
[9 ] 丁金立,王志平,卓芝政,等.2D-SSh-MRCP序列与基于压缩 感知技术的CS-3D-MRCP序列在胰胆管成像中的对比研究 [J].北京生物医学工程,2020,39(3) :290-295.
Ding JL, Wang ZP, Zhuo ZZ, et al. Comparison of 2D — SSh — MRCP and compressed sensing sensitivity encoding based CS— 3D—MRCP in cholangiopancreatography [ J ]. Beijing Biomedical Engineering, 2020,39(3) : 290—295.
[10]?李青,鲁珊珊,孙涛,等.压缩感知技术在头颅磁共振血管成 像中的应用研究[J].中国医学装备,2020,17(2) :66-70.
Li Q, Lu SS, Sun T, et al. The applied research on the CS technique in intracranial MRA [ J]. China Medical Equipment, 2020,17(2) :66-70.
[11]?孔欢,束月霞,刘欣.基于光学波动和压缩感知的超分辨超声 成像研究[J].医疗卫生装备,2019,40(9) :8-11.
Kong H, Shu YX, Liu X, Super-resolution ultrasound imaging based on optical fluctuation and compressed sensingf J]. Chinese Medical Equipment Journal,2019,40(9) :8—11.
[12]?董昕,陈思佳,李军.基于压缩感知和散斑相关法的散射介质 成像方法研究[J].激光生物学报,2019,28(1) =64-71.
Dong X, Chen SJ, Li J. Research on scattering medium imaging method based on compressive sensing and speckle correlation [J]. Acta Laser Biology Sinica,2019,28(1) : 64-71.
[13]?郭庆,滕月阳,仝灿,等.基于压缩感知与快速迭代阈值收缩算 法的脑功能网络重建[J].生物医学工程学杂志,2020,37 (5) :855-862.
Guo Q, Teng YY, Tong C, et al. Brain functional network reconstruction based on compressed sensing and fast iterative shrinkage-thresholding algorithm [ J ]. Journal of Biomedical Engineering,2020,37(5) :855-862.
[14]?魏强,王家正,伊东娜,等.结合压缩感知技术与敏感度编码的 3D mDixon序列以及3D Vane序列对肝脏成像的影响的对比 研究[J].磁共振成像,2020,11(9) :781-785.
Wei Q,Wang JZ,Yi DN,et al. A comparative study on the effects of 3D mDixon sequence and 3D Vane sequence on liver imaging by combining the Compressed SENSE technology and SENSE] J]. Chinese Journal of Magnetic Resonance Imaging, 2020,11 (9): 781-785.
[15]?向逾,黄飞,何清.基于三维决策空间的医疗设备维修策略研 究[J].医疗卫生装备,2019,40(12) :61-64.
Xiang Y, Huang F, He Q. Research on medical equipment maintenance strategies based on 3D decision space [ J]. Chinese Medical Equipment Journal,2019,40( 12) :61—64
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