小曲率半径医学图像快速三维重构算法研究
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摘要
针对小曲率半径医学器官图像表面不具有明显的特征,无法采用自由拼接,排序过程耗时严重,图像重构过程坐标失真、毛刺较多的问题。提出了一种医学图像曲面混乱区域配准方法,对小曲率半径图像三维坐标空间变换参数进行改进,在改进过程中采将坐标误差可接受程度收敛至最优值附近。摒弃传统的排序拼接思维。由后期需要融合的医学三维图像曲面分别进行小波分解及小波逆变换,重构得到高清晰医学图像三维曲面。试验结果表明:医学图像三维可视化绘制中,在不具备明显特征条件下,绘制时间缩短,融合后图像清晰度高。
Since there is no obvious characteristics on the surface of medical image with small curvature radius,problems will be encountered,including impossibility of image stitching,large time-consumption in image sequencing,coordinate distortion and formation of burr in image reconstruction process. To this end,a registration method for chaotic area of medical image surface was proposed to improve the 3 D coordinate space transformation parameter of medical image with small curvature radius. In improvement process,the acceptability of coordinate error was converged to the optimal value. The traditional thoughts on image sequencing and stitching were abandoned in this study,instead the 3 D medical images were successively subjected to wavelet decomposition and inverse wavelets transform before being fused,resulting in high-definition 3 D surface of medical image. Results showed that the 3 D visual drawing of medical image shortened the drawing time and improved the definition of post-fusion image even thought there is no obvious characteristics on the surface of medical image with small curvature radius.
Since there is no obvious characteristics on the surface of medical image with small curvature radius,problems will be encountered,including impossibility of image stitching,large time-consumption in image sequencing,coordinate distortion and formation of burr in image reconstruction process. To this end,a registration method for chaotic area of medical image surface was proposed to improve the 3 D coordinate space transformation parameter of medical image with small curvature radius. In improvement process,the acceptability of coordinate error was converged to the optimal value. The traditional thoughts on image sequencing and stitching were abandoned in this study,instead the 3 D medical images were successively subjected to wavelet decomposition and inverse wavelets transform before being fused,resulting in high-definition 3 D surface of medical image. Results showed that the 3 D visual drawing of medical image shortened the drawing time and improved the definition of post-fusion image even thought there is no obvious characteristics on the surface of medical image with small curvature radius.
引文
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[2]Dong H,Kervran Y,Coulon N,et al.Highly Flexible Microcrystalline Silicon n-Type TFT on PEN Bent to a Curvature Radius of 0.75 mm[J].IEEE Transactions on Electron Devices,2015,62(10):3278-3284.
[3]周娟.基于MITK的医学图像三维表面重建算法[J].计算机科学,2016,43(S1):194-197.
[4]丰焕亭,陈春阳.虚拟医学解剖实验的关键方法仿真[J].计算机仿真,2016,33(4):411-414.
[5]Hill D E,Hopkins D F.Effect of small radius of curvature on transonic flow in axisymmetric nozzles.[J].Aiaa Journal,2015,4(8):1337-1343.
[6]范阳阳,倪倩,温铁祥,等.Freehand三维超声体数据重建的最新研究进展[J].中国生物医学工程学报,2017,36(1):92-102.
[7]罗敏,李辉.低照度条件下超分辨率人脸图像采集系统设计与实现[J].计算机测量与控制,2016,24(11):229-231.
[8]Dong H,Kervran Y,Coulon N,et al.Highly Flexible Microcrystalline Silicon n-Type TFT on PEN Bent to a Curvature Radius of 0.75 mm[J].IEEE Transactions on Electron Devices,2015,62(10):3278-3284.
[9]任立胜,王立中.基于曲率尺度空间的角点检测图像匹配算法分析[J].电子技术应用,2016,42(12):112-114.
[10]Jie M,Xi H,Fan W.The effects of thermal field on radius of curvature interferometric testing[J].Optical Review,2015,22(2):299-307.
[11]陈正兵.基于深度图像的室内三维平面分割方法研究[J].电子设计工程,2016,24(24):158-160.
[12]陈思思,朱德喜,马庆凯,等.基于谱域OCT图像的人眼前节生物学参数自动测量[J].中华实验眼科杂志,2016,34(4):345-350.
[13]金显华,睢丹.基于拟蒙特卡罗和Taubin平滑的三维图像重构算法[J].微电子学与计算机,2015(8):163-166.
[14]赵志升,张晓,梁俊花,等.融入背景差分连续重构的心脏医学图像重建[J].科技通报,2015,31(8):207-209.
[15]赵龙,韦群.序列图像三维重构中点云精简算法的研究与改进[J].计算机工程与应用,2016,52(8):211-216.
[16]Hoffmann M,Brost A,Koch M,et al.Electrophysiology Catheter Detection and Reconstruction from Two Views in Fluoroscopic Images.[J].IEEE Transactions on Medical Imaging,2016,35(2):567.
[17]尹阳,刘君.重击下颅骨CT图像裂痕区域检测方法研究[J].计算机仿真,2016,33(12):366-369.
[18]Losada M A,López A,Mateo J.Attenuation and diffusion produced by small-radius curvatures in POFs.[J].Optics Express,2016,24(14):15710.
[19]Ericson E A,Lyzenga D R.Performance of a numerical iterative solution of the surface current integral equation for surfaces containing small radii of curvature[J].Radio Science,2016,33(2):205-217.
[20]谌湘倩,马绍惠,须文波.基于有序子集加速拆分算法的三维CT图像重建[J].现代电子技术,2016,39(6):104-107.