光学 精密工程, 2017, 25 (4): 1106, 网络出版: 2017-06-02   

基于稀疏处理的多能X射线分离成像

Separation of multi-energy X-ray imaging based on sparse processing
作者单位
1 南京邮电大学 光电工程学院, 江苏 南京 210023
2 南京理工大学 电子工程与光电技术学院, 江苏 南京 210094
引用该论文

费彬, 孙京阳, 张俊举, 喻春雨. 基于稀疏处理的多能X射线分离成像[J]. 光学 精密工程, 2017, 25(4): 1106.

FEI Bin, SUN Jing-yang, ZHANG Jun-ju, YU Chun-yu. Separation of multi-energy X-ray imaging based on sparse processing[J]. Optics and Precision Engineering, 2017, 25(4): 1106.

参考文献

[1] MCCOLLOUGH CH,LENG SA, YU L F,et al.. Dual- and multi-energy CT: principles, technical approaches, and clinical applications [J]. Radiology, 2015, 276(3): 637-653.

[2] RICHARD K J, RICHARD A K. Application of high resolution X-ray computed tomography to mineral deposit origin, evaluation, and processing [J]. Ore Geology Reviews, 2015, 65(SI): 821-839.

[3] STUTMAN D, TRITZ K, FINKENTHAL M. Multi-energy x-ray imaging and sensing for diagnostic and control of the burning plasma [J]. Review of Scientific Instruments, 2012, 83(10): 10E535.

[4] SAIM A,TEBBOUNE A,BERKOK H, et al.. Linear and mass attenuation coefficient for CdTe compound of X-rays from 10 to 100 keV energy range in different phases [J]. Journal of Alloys and Compounds, 2014, 602: 261-264.

[5] MIDGLEY SM. A model for multi-energy x-ray analysis [J]. Physics in Medicine and Biology, 2011,56(10): 2943-2962.

[6] FIRSCHING M,NACHTRAB F,UHLMANN N,et al.. Multi-energy X-ray imaging as a quantitative method for materials characterization [J]. Advanced Materials, 2011, 23(22-23): 2655-2656.

[7] 李艳, 喻春雨, 缪亚健, 等. 基于ICA的X射线医学图像目标提取[J].光谱学与光谱分析,2015,35(3): 825-828.

    LI Y, YU CH Y, MIAO Y J, et al.. Object separation from medical x-ray images based on ICA [J]. Spectroscopy and Spectral Analysis, 2015, 35(3), 825-828. (in Chinese)

[8] HYVARINEN A. Independent component analysis: Recent advances [J]. Philosophical Transactions of the Royal Society A, 2013,371(1984): 20110534.

[9] 陈媛媛, 王芳, 王志斌, 等. 独立成分分析在化学战剂混叠峰识别中的应用[J]. 红外与激光工程, 2016, 45(4): 0423001.

    CHEN Y Y, WANG F, WANG ZH B, et al.. Application of independent component analysis in aliasing peak identification of chemical warfare agents [J]. Infrared and Laser Engineering, 2016, 45(4): 0423001.(in Chinese)

[10] DONOHO D L. Compressed sensing [J]. IEEE Transactions on Information Theory, 2006, 52(4): 1289-1306.

[11] 酉霞, 陈菲, 贾小林, 等.字典学习中字典尺度对 DICOM 图像压缩的影响[J].液晶与显示, 2015, 30(6): 1045-1050.

    YOU X, CHEN F, JIA X L, et al.. Effects of dictionary scale on dictionary learning for DICOM image compression [J].Chinese Journal of Liquid Crystals and Displays, 2015, 30(6): 1045-1050. (in Chinese)

[12] 周渝人,耿爱辉,张强.基于压缩感知的红外与可见光图像融合[J].光学 精密工程,2015,23(3): 855-863.

    ZHOU Y R, GENG A H, ZHANG Q, et al.. Fusion of infrared and visible images based on compressive sensing[J]. Opt. Precision Eng., 2015,23(3): 855-863. (in Chinese)

[13] WU Z Y, ZHANG W, WANG J W, et al.. Feature extraction for gas photoacoustic spectroscopy and content inverse based on overcomplete ICA bases [J]. Optics and Laser Technology, 2013, 48: 580-588.

[14] PENG H Y, ZHU S M. Handling of incomplete data sets using ICA and SOM in data mining [J]. Neural Computing& Applications, 2007, 16(2): 167-172.

[15] EMMANUEL C J,ROMBERG J, TAO T. Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information [J]. IEEE Transactions on Information Theory, 2006, 52(2): 489-509.

[16] RABAH H, AMIRA A, MOHANTY B K,et al.. FPGA implementation of orthogonal matching pursuit for compressive sensing reconstruction [J]. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2015,23(10): 2209-2220.

[17] PTUCHA R,SAVAKIS A E. LGE-KSVD: Robust sparse representation classification [J]. IEEE Transactions on Image Processing, 2014,23(4): 1737-1750.

费彬, 孙京阳, 张俊举, 喻春雨. 基于稀疏处理的多能X射线分离成像[J]. 光学 精密工程, 2017, 25(4): 1106. FEI Bin, SUN Jing-yang, ZHANG Jun-ju, YU Chun-yu. Separation of multi-energy X-ray imaging based on sparse processing[J]. Optics and Precision Engineering, 2017, 25(4): 1106.

本文已被 3 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!