多层螺旋CT处理技术在脊柱侧弯图像三维重建中的应用
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摘要
现代医学图像,尤其是脊柱侧弯图像的三维重建特征点识别精度较低。对此,在传统三维重建图像基础上应用多层螺旋CT处理技术,进行技术优化。首先通过多层螺旋CT处理技术将三维数据进行投影,建立高斯特征点尺度空间;利用SIFT特征点算法,对尺度空间极值进行检测,从而定位特征点并分配特征点方向,生成关键点描述子,匹配特征向量;为了提高三维图像特征点精度,引入对极几何与基础矩阵,利用多层螺旋CT处理技术进行系统评价,剔除错误匹配点;最后利用多层螺旋CT处理技术的多平面曲面处理技术和相继模型,完成脊柱侧弯图像的相机标定和三维重建。实验数据表明,与传统三维重建技术相比,应用多层螺旋CT处理技术后,三维重建图像稠密点数量明显提高了47%,图像角点匹配率提高25. 5%,明显提高了识别精度。
The recognition accuracy of 3 d reconstruction feature points of modern medical images,especially those of scoliosis images,is relatively low. Based on the application of multi-slice CT processing technology,the 3 d reconstruction technology of PMVS scoliosis images is designed. Firstly,the 3 d data is projected by multi-slice spiral CT processing technology,and the gaussian feature point scale space is established. Through the SIFT feature point algorithm,the extreme value of scale space and the location of feature points are detected,and the direction of feature points is allocated to generate the key point descriptor and match the feature vector. In order to improve the accuracy of feature points of 3 d images,polar geometry and basic matrix are introduced and error matching points are proposed. Finally,the camera calibration and 3 d reconstruction of scoliosis images were completed by using the multi-slice curved surface processing technology and successive model of multi-slice spiral CT. Experimental data shows that compared with traditional 3 d reconstruction technology,PMVS 3 d reconstruction technology has significantly increased the number of dense points in the reconstruction image by 47%,and the image angular point matching rate by 25. 5%,which has significantly improved the recognition accuracy.
The recognition accuracy of 3 d reconstruction feature points of modern medical images,especially those of scoliosis images,is relatively low. Based on the application of multi-slice CT processing technology,the 3 d reconstruction technology of PMVS scoliosis images is designed. Firstly,the 3 d data is projected by multi-slice spiral CT processing technology,and the gaussian feature point scale space is established. Through the SIFT feature point algorithm,the extreme value of scale space and the location of feature points are detected,and the direction of feature points is allocated to generate the key point descriptor and match the feature vector. In order to improve the accuracy of feature points of 3 d images,polar geometry and basic matrix are introduced and error matching points are proposed. Finally,the camera calibration and 3 d reconstruction of scoliosis images were completed by using the multi-slice curved surface processing technology and successive model of multi-slice spiral CT. Experimental data shows that compared with traditional 3 d reconstruction technology,PMVS 3 d reconstruction technology has significantly increased the number of dense points in the reconstruction image by 47%,and the image angular point matching rate by 25. 5%,which has significantly improved the recognition accuracy.
引文
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[2]王诗军,李钰婷,李淳德.脊柱侧弯内固定系统置入及三维重建技术的应用[J].中国组织工程研究,2016,20(4):583-588.
[3]路光普,叶金铎,冯晶晶,等.漏斗胸与脊柱侧弯同时矫形对胸廓变形影响的数值模拟[J].中国组织工程研究,2017,21(19):3017-3022.
[4]王超,赵文峰,刘丽,等.脊柱侧弯患者下颌骨的三维形态分析[J].现代生物医学进展,2016,16(2):335-338.
[5]侯永威,叶金铎,董黎敏,等.基于计算的漏斗胸合并脊柱侧弯微创矫形手术方案的研究与临床[J].天津理工大学学报,2016,32(5):21-25.
[6]王涛,林伟,史铁钧,等.142例脊髓纵裂合并骨性分隔患者的临床诊疗探讨[J].中华神经外科疾病研究杂志,2017,16(5):397-401.
[7]孙记航,阴捷,刘志敏,等.基于模型的迭代重建算法应用于80kV低剂量儿童胸部CT的可行性[J].中国医学影像技术,2017,33(4):599-602.
[8]刘琴,王秋霞,万常华,等.先天性脊柱侧弯矫治术前全脊柱三维磁共振成像的价值[J].放射学实践,2017,32(2):175-178.
[9]裴冬阳,饶耀剑.国内Ilizarov技术在脊柱侧弯方向的临床应用现状[J].中医临床研究,2016,8(1):147-148.
[10]董本清,彭健钧.复杂网络数据流中的异常数据挖掘算法仿真[J].计算机仿真,2016,33(1):434-437.
[11]王其飞,杨军林,黄紫房,等.Lenke I型脊柱侧弯肩部平衡的2年随访研究[J].中国矫形外科杂志,2016,24(17):1575-1580.
[12]李波,张辉琴,桂钱欢,等.青少年腰骶部半椎体所致僵硬脊柱侧弯冠状面矫治的疗效观察[J].重庆医学,2016,45(36):5104-5106.
[13]张毅杰,陈雁西,张坤,等.基于CT三维重建图像的胫骨平台形态学研究及其临床意义[J].中华创伤杂志,2017,33(1):63-68.
[14]申超群,高静.基于VTK的SRM断面图像三维重建系统构建[J].计算机仿真,2016,33(3):90-94.
[15]付廷刚,张静,黄忠浩,等.探索建立颅脑MRI图像、断层标本图像及三维重建图像的对比数据模型[J].解剖学报,2016,47(2):243-246.