激光与光电子学进展, 2018, 55 (10): 101701, 网络出版: 2018-10-14  

用于定位激发平面的混合高斯方法

Location Method of Excitation Planes Based on Gaussian Mixture Distribution
作者单位
西北大学信息科学与技术学院, 陕西 西安 710127
引用该论文

王晓东, 耿国华, 易黄建, 何雪磊, 贺小伟. 用于定位激发平面的混合高斯方法[J]. 激光与光电子学进展, 2018, 55(10): 101701.

Wang Xiaodong, Geng Guohua, Yi Huangjian, He Xuelei, He Xiaowei. Location Method of Excitation Planes Based on Gaussian Mixture Distribution[J]. Laser & Optoelectronics Progress, 2018, 55(10): 101701.

参考文献

[1] Ntziachristos V, Tung C H, Bremer C, et al. Fluorescence molecular tomography resolves protease activity in vivo[J]. Nature Medicine, 2002, 8: 757-761.

[2] Ale A, Ermolayev V, Herzog E,et al. FMT-XCT: in vivo animal studies with hybrid fluorescence molecular tomography-X-ray computed tomography[J]. Nature Methods, 2012, 9: 615-620.

[3] Tian J. Molecular imaging[M]. Hangzhou: Zhejiang University Press, 2013: 185-216.

[4] He X L, Wang X D, Yi H J, et al. Laplacian manifold regularization method for fluorescence molecular tomography[J]. Journal of Biomedical Optics, 2017, 22(4): 045009.

[5] Guo H B, Yu J J, He X W, et al. Improved sparse reconstruction for fluorescence molecular tomography with L1/2 regularization[J]. Biomedical Optics Express, 2015, 6(5): 1648-1664.

[6] 侯榆青, 魏红娜, 易黄建, 等. 螺旋式激发的荧光分子断层成像[J]. 西安电子科技大学学报(自然科学版), 2018, 45(2): 97-102.

    Hou Y Q, Wei H N, Yi H J, et al. Imaging system of fluorescence molecular tomography with spiral excitation[J]. Journal of Xidian University (Natural Science), 2018, 45(2): 97-102.

[7] Zhu D W, Li C Q. Nonconvex regularizations in fluorescence molecular tomography for sparsity enhancement[J]. Physics in Medicine and Biology, 2014, 59(12): 2901-2912.

[8] Chen D F, Liang J M, Li Y, et al. A sparsity-constrained preconditioned Kaczmarz reconstruction method for fluorescence molecular tomography[J]. BioMed Research International, 2016, 2016: 4504161.

[9] An Y, Liu J, Zhang G L, et al. A novel region reconstruction method for fluorescence molecular tomography[J]. IEEE Transactions on Biomedical Engineering, 2015, 62(7): 1818-1826.

[10] Wu Z T, Wang X D, Yu J, J, et al. Synchronization-based clustering algorithm for reconstruction of multiple reconstructed targets in fluorescence molecular tomography[J]. Journal of the Optical Society of America A, 2018, 35(2): 328-335.

[11] Han D, Tian J, Zhu S P, et al. A fast reconstruction algorithm for fluorescence molecular tomography with sparsity regularization[J]. Optics Express, 2010, 18(8): 8630-8646.

[12] Cong A, Wang G. A finite-element-based reconstruction method for 3D fluorescence tomography[J]. Optics Express, 2005, 13(24): 9847-9857.

[13] Wang D F, Liu X, Chen Y P, et al. A novel finite-element-based algorithm for fluorescence molecular tomography of heterogeneous media[J]. IEEE Transactions on Information Technology in Biomedicine, 2009, 13(5): 766-773.

[14] Cong W X, Wang G, Kumar D, et al. Practical reconstruction method for bioluminescence tomography[J]. Optics Express, 2005, 13(18): 6756-6771.

[15] 易黄建. 基于正则化的荧光分子断层成像重建方法研究[D]. 西安: 西安电子科技大学, 2013: 15-31.

    Yi H J. Regularization based reconstruction algorithms for fluorescence molecular tomography[D]. Xi′an: Xidian University, 2013: 15-31.

[16] Bishop C. Pattern recognition and machine learning[M]. New York: Springer, 2006: 430-439.

[17] Dogdas B, Stout D, Chatziioannou A F, et al. Digimouse: a 3D whole body mouse atlas from CT and cryosection data[J]. Physics in Medicine & Biology, 2007, 52(3): 577-587.

[18] 刘合娟, 侯榆青, 贺小伟, 等. 几种典型迭代算法在生物发光断层成像中的对比研究及评估[J]. 激光与光电子学进展, 2015, 52(8): 081704.

    Liu H J, Hou Y Q, He X W, et al. A comparative study and evaluation on several typical iterative methods for bioluminescence tomography[J]. Laser & Optoelectronics Progress, 2015, 52(8), 52: 081704.

[19] 董芳, 侯榆青, 余景景, 等. 结合区域收缩和贪婪策略的荧光分子断层成像[J]. 激光与光电子学进展, 2016, 53(1): 011701.

    Dong F, Hou Y Q, Yu J J, et al. Fluorescence molecular tomography via greedy method combined with region-shrinking strategy[J]. Laser & Optoelectronics Progress, 2016, 53(1): 011701.

[20] 侯榆青, 金明阳, 贺小伟, 等. 基于随机变量交替方向乘子法的荧光分子断层成像[J]. 光学学报, 2017, 37(7): 0717001.

    Hou Y Q, Jin M Y, He X W, et al. Fluorescence molecular tomography using a stochastic variant of alternating direction method of multipliers[J]. Acta Optica Sinica, 2017, 37(7): 0717001.

[21] He X W, Liang J M, Wang X R, et al. Sparse reconstruction for quantitative bioluminescence tomography based on the incomplete variables truncated conjugate gradient method[J]. Optics Express, 2010, 18(24): 24825-24841.

[22] Wang X D, Liu F, Jiao L C, et al. Incomplete variables truncated conjugate gradient method for signal reconstruction in compressed sensing[J]. Information Sciences, 2014, 288(20): 387-411.

[23] 张海波, 耿国华, 赵映程, 等. 基于非凸L1-2正则子的锥束X射线发光断层成像[J]. 光学学报, 2017, 37(6): 0617001.

    Zhang H B, Geng G H, Zhao Y C, et al. Nonconvex L1-2 regularization for fast cone-beam X-ray luminescence computed tomography[J]. Acta Optica Sinica, 2017, 37(6): 0617001.

[24] 张旭, 易黄建, 侯榆青, 等. 基于局部保留投影的荧光分子断层成像快速重建[J]. 光学学报, 2016, 36(7): 0717001.

    Zhang X, Yi H J, Hou Y Q, et al. Fast reconstruction in fluorescence molecular tomography based on locality preserving projections[J]. Acta Optica Sinica, 2016, 36(7): 0717001.

[25] Song X M, Pogue B W, Jiang S D, et al. Automated region detection based on the contrast-to-noise ratio in near-infrared tomography[J]. Applied Optics, 2004, 43(5): 1053-1062.

王晓东, 耿国华, 易黄建, 何雪磊, 贺小伟. 用于定位激发平面的混合高斯方法[J]. 激光与光电子学进展, 2018, 55(10): 101701. Wang Xiaodong, Geng Guohua, Yi Huangjian, He Xuelei, He Xiaowei. Location Method of Excitation Planes Based on Gaussian Mixture Distribution[J]. Laser & Optoelectronics Progress, 2018, 55(10): 101701.

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!