基于z轴权重的麦粒图像三维重建
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摘要
为得到清晰的麦粒重建切片,利用共轭射线弥补Radon空间数据缺失,在FDK(Feldkamp-Davis-Kress)重建算法的基础上,引入z轴权重函数来优化麦粒切片图像的重建结果。针对三维头模型,z-FDK算法重建结果的均方根误差比FDK算法的小3.6927,大大抑制了FDK算法中的z轴方向强度下降。实验结果表明,针对卵期、低龄幼虫期和高龄幼虫期的麦粒投影图像,z-FDK算法的平均梯度和对比度噪声比均大于FDK算法,重建麦粒茸毛端和胚部端两个区域的灰度值增大,伪影得到改善。
In order to obtain clear wheat grain reconstruction slices, the conjugated ray is used to compensate for the missing data of Radon space. Based on the FDK(Feldkamp-Davis-Kress) reconstruction algorithm, the z-axis weight function is introduced to optimize the reconstruction results of the grain slice images. For the three-dimensional head model, the root mean squared error of the reconstruction result by the z-FDK algorithm is 3.6927 smaller than that of the FDK algorithm and the z-axis strength drop in the FDK algorithm is greatly suppressed. As for the projection images of wheat grains at egg stage, young larva stage and old larva stage, the experimental results show that the average gradient and the contrast noise ratio of the z-FDK algorithm are both larger than those of the FDK algorithm. The gray values of the reconstructed two regions of the hair end and the embryo end of wheat grains increase and the artifacts are improved.
In order to obtain clear wheat grain reconstruction slices, the conjugated ray is used to compensate for the missing data of Radon space. Based on the FDK(Feldkamp-Davis-Kress) reconstruction algorithm, the z-axis weight function is introduced to optimize the reconstruction results of the grain slice images. For the three-dimensional head model, the root mean squared error of the reconstruction result by the z-FDK algorithm is 3.6927 smaller than that of the FDK algorithm and the z-axis strength drop in the FDK algorithm is greatly suppressed. As for the projection images of wheat grains at egg stage, young larva stage and old larva stage, the experimental results show that the average gradient and the contrast noise ratio of the z-FDK algorithm are both larger than those of the FDK algorithm. The gray values of the reconstructed two regions of the hair end and the embryo end of wheat grains increase and the artifacts are improved.
引文
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[23] Yang Y F, Zhang D H, Huang K D, et al. Three-dimensional weighting reconstruction algorithm for circular cone-beam CT under large scan angles[J]. Nuclear Science and Techniques, 2017, 28(8): 116.
[24] Huang K, Chen P, Liu W W, et al. Dictionary learning based recovery algorithm for sparse-view sampling photoacoustic data[J]. Acta Optica Sinica, 2018, 38(11): 1117002. 黄凯, 陈平, 刘伟伟, 林列. 基于字典学习的稀疏角度采样光声信号重建[J]. 光学学报, 2018, 38(11): 1117002.
[25] Zhao Q, Wang Y H, Gao X Y, et al. Filtering evaluation method of phase images based on smooth spline fitting[J]. Acta Optica Sinica, 2018, 38(8): 0815020. 赵琪涵, 王永红, 高新亚, 等. 基于平滑样条拟合的相位图像滤波评价方法[J]. 光学学报, 2018, 38(8): 0815020.
[2] Zhang H T, Mao H P, Ju S, et al. Automatic posture recognition of wheat kernels based on germ features[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(14): 163-169. 张红涛, 毛罕平, 剧森, 等. 基于胚部区域特征的麦粒姿态自动识别[J]. 农业工程学报, 2014, 30(14): 163-169.
[3] Jian F J, Jayas D S, Fields P G, et al. A new method to rapidly detect rusty grain beetle, Cryptolestes ferrugineus (Stephens), in stored grain[J]. Journal of Stored Products Research, 2015, 63: 1-5.
[4] Hu H J. Discussion on present situation and problems of of stored-grain pests control[J]. Modern Food, 2017, 7(14): 4-5. 胡红军. 储粮害虫防治现状及问题讨论[J]. 现代食品, 2017, 7(14): 4-5.
[5] Tang P A, Hou X Y, Kong D Y, et al. Research on the technology of electronic nose to detect the density and state of maize weevil[J]. Journal of the Chinese Cereals and Oils Association, 2015, 30(12): 87-91, 97. 唐培安, 侯晓燕, 孔德英, 等. 电子鼻检测玉米象不同虫态的技术研究[J]. 中国粮油学报, 2015, 30(12): 87-91, 97.
[6] Gao H, Zhu Y H, Zhen T. Present situation and prospects of detection technology of stored-grain insects[J]. Science and Technology of Cereals, Oils and Foods, 2016, 24(2): 93-96. 高华, 祝玉华, 甄彤. 仓储害虫检测技术的研究现状及展望[J]. 粮油食品科技, 2016, 24(2): 93-96.
[7] Eliopoulos P A, Potamitis I, Kontodimas D C, et al. Detection of adult beetles inside the stored wheat mass based on their acoustic emissions[J]. Journal of Economic Entomology, 2015, 108(6): 2808-2814.
[8] Piasecka-Kwiatkowska D, Nawrot J, Zielińska-Dawidziak M, et al. Detection of grain infestation caused by the granary weevil (Sitophilus granarius L.) using zymography for α-amylase activity[J]. Journal of Stored Products Research, 2014, 56: 43-48.
[9] Verboven P, Herremans E, Borisjuk L, et al. Void space inside the developing seed of Brassica napus and the modelling of its function[J]. New Phytologist, 2013, 199(4): 936-947.
[10] Liu D T, Wang Z, Yan D W, et al. Advances in the pathway and visualization study of water transport in grain[J]. Plant Physiology Journal, 2017, 53(11): 1947-1954. 刘大同, 王忠, 闫大伟, 等. 作物籽粒中水分运输路径及其可视化研究进展[J]. 植物生理学报, 2017, 53(11): 1947-1954.
[11] Devarrewaere W, Foqué D, Heimbach U, et al. Quantitative 3D shape description of dust particles from treated seeds by means of X-ray micro-CT[J]. Environmental Science & Technology, 2015, 49(12): 7310-7318.
[12] Suresh A, Neethirajan S. Real-time 3D visualization and quantitative analysis of internal structure of wheat kernels[J]. Journal of Cereal Science, 2015, 63: 81-87.
[13] Strange H, Zwiggelaar R, Sturrock C, et al. Automatic estimation of wheat grain morphometry from computed tomography data[J]. Functional Plant Biology, 2015, 42(5): 452-459.
[14] Guelpa A, du Plessis A, Manley M. A high-throughput X-ray micro-computed tomography (μCT) approach for measuring single kernel maize (Zea mays L.) volumes and densities[J]. Journal of Cereal Science, 2016, 69: 321-328.
[15] Schoeman L, du Plessis A, Verboven P, et al. Effect of oven and forced convection continuous tumble (FCCT) roasting on the microstructure and dry milling properties of white maize[J]. Innovative Food Science & Emerging Technologies, 2017, 44: 54-66.
[16] Warning A, Verboven P, Nicola? B, et al. Computation of mass transport properties of apple and rice from X-ray microtomography images[J]. Innovative Food Science & Emerging Technologies, 2014, 24(8): 14-27.
[17] Chen S R, Xu L, Yin J J, et al. Quantitative characterization of grain internal damage and 3D reconstruction based on Micro-CT image processing[J]. Transactions of the Chinese Society of Agricultural Engineering, 2017, 33(17): 144-151. 陈树人, 徐李, 尹建军, 等. 基于Micro-CT图像处理的稻谷内部损伤定量表征与三维重构[J]. 农业工程学报, 2017, 33(17): 144-151.
[18] Li Z G, Li L, Han Y, et al. Backprojection filtering reconstruction algorithm for circle-plus-line trajectory in cone beam CT[J]. Acta Optica Sinica, 2016, 36(9): 0911008. 李增光, 李磊, 韩玉, 等. 锥束CT圆加直线轨迹反投影滤波重建算法[J]. 光学学报, 2016, 36(9): 0911008.
[19] Yang Y F, Zhang D H, Huang K D, et al. Three-dimensional weighting reconstruction algorithm for cone-beam CT based on ellipsoidal bounding box[J]. Chinese Journal of Scientific Instrument, 2016, 37(11): 2563-2571. 杨亚飞, 张定华, 黄魁东, 等. 基于椭球包围盒的锥束CT三维加权重建算法[J]. 仪器仪表学报, 2016, 37(11): 2563-2571.
[20] Feldkamp L A, Davis L C, Kress J W . Practical cone-beam algorithm[J]. Journal of the Optical Society of America A, 1984, 1(6): 612-619.
[21] Zhu L, Starman J, Fahrig R. An efficient estimation method for reducing the axial intensity drop in circular cone-beam CT[J]. International Journal of Biomedical Imaging, 2008, 2008: 242841.
[22] Chen Z K, Calhoun V D, Chang S J. Compensating the intensity fall-off effect in cone-beam tomography by an empirical weight formula[J]. Applied Optics, 2008, 47(32): 6033-6039.
[23] Yang Y F, Zhang D H, Huang K D, et al. Three-dimensional weighting reconstruction algorithm for circular cone-beam CT under large scan angles[J]. Nuclear Science and Techniques, 2017, 28(8): 116.
[24] Huang K, Chen P, Liu W W, et al. Dictionary learning based recovery algorithm for sparse-view sampling photoacoustic data[J]. Acta Optica Sinica, 2018, 38(11): 1117002. 黄凯, 陈平, 刘伟伟, 林列. 基于字典学习的稀疏角度采样光声信号重建[J]. 光学学报, 2018, 38(11): 1117002.
[25] Zhao Q, Wang Y H, Gao X Y, et al. Filtering evaluation method of phase images based on smooth spline fitting[J]. Acta Optica Sinica, 2018, 38(8): 0815020. 赵琪涵, 王永红, 高新亚, 等. 基于平滑样条拟合的相位图像滤波评价方法[J]. 光学学报, 2018, 38(8): 0815020.