基于CT图像的全髋关节置换辅助诊断算法
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摘要
计算机辅助诊断算法是医学图像处理领域的研究热门。全髋关节置换前医生需要手动对比CT与股骨柄图像进行诊断。提出了一种基于CT图像的人工髋关节置换辅助诊断算法。首先统一CT图像与人工髋关节图像的度量;然后通过图像处理提取CT中股骨头中心与股骨干轴线作为内部基准;最后根据基准对人工髋关节图像进行几何变换,与CT图像融合后以模拟植入后效果,辅助医生诊断。实验结果表明,该算法能够准确地将人工髋关节图像与CT图像配准。
Computer-aided diagnosis algorithms are popular in the field of medical image processing. Before total hip replacement,doctors need to manually compare CT and femoral stem images for diagnosis. An artificial hip joint replacement diagnosis algorithm based on CT image is proposed. First,the metrics of the CT image and the artificial hip joint image are unified. The image of the femoral head center and the femoral shaft axis in the CT is then extracted as an internal reference by image processing. Finally,the artificial hip joint image is geometrically transformed according to the reference,merging with CT images to simulate post-implantation effects,in order to assist doctors in diagnosis. The experimental results show that the algorithm can accurately register the artificial hip joint image with the CT image.
Computer-aided diagnosis algorithms are popular in the field of medical image processing. Before total hip replacement,doctors need to manually compare CT and femoral stem images for diagnosis. An artificial hip joint replacement diagnosis algorithm based on CT image is proposed. First,the metrics of the CT image and the artificial hip joint image are unified. The image of the femoral head center and the femoral shaft axis in the CT is then extracted as an internal reference by image processing. Finally,the artificial hip joint image is geometrically transformed according to the reference,merging with CT images to simulate post-implantation effects,in order to assist doctors in diagnosis. The experimental results show that the algorithm can accurately register the artificial hip joint image with the CT image.
引文
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3李宏,孙航,刘圣楠,等.基于3D-CT图像的髋脱位定量智能诊断方法[J].东北大学学报(自然科学版),2018,39(2):190-194Li Hong,Sun Hang,Liu Shengnan,et al.Quantitative and intelligent diagnosis method of hip dislocation based on 3D-CT images[J].Journal of Northeastern University(Natural Science),2018,39(2):190-194
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6 Li B,Lu H,Cai W,et al.Computer aided diagnosis and treatment planning for development dysplasis of the hip[J].Proceeding of SPIE-The International Society for Optical Engineering,2005,5744:781-788
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8 Tavakoli V,Amini A A.A survey of shaped-based registration and segmentation techniques for cardiac images[J].Computer Vision&Image Understanding Cviu,2013,117(9):966-989
9 Nishihara S,Fujita H,Iida T,et al.Computer-aided diagnosis if osteoporosis using abdominal X-ray CT images:Preliminary study of automated region extraction and comparison between BMD values and CT features[J].Transactions of the Japanese Society for Medical&Biological Engineering Bme,2004,42:7-15
10 Terry Canale S,Beaty J H.坎贝尔骨科手术学[M].12版.王岩,译.北京:人民军医出版社.2013:172-174Terry Canale S.Beaty J H.Campbell’s operative orthopaedics[M].12th ed.Wang Yan,translated.Beijing:People’s Military Medical Press,2013:172-174
2罗率力.基于医学诊断的模糊专家系统技术研究[D].长沙:湖南大学,2012Luo Shuaili.The medical diagnosis based on fuzzy expert system technology research[D].Changsha:Hunan University,2012
3李宏,孙航,刘圣楠,等.基于3D-CT图像的髋脱位定量智能诊断方法[J].东北大学学报(自然科学版),2018,39(2):190-194Li Hong,Sun Hang,Liu Shengnan,et al.Quantitative and intelligent diagnosis method of hip dislocation based on 3D-CT images[J].Journal of Northeastern University(Natural Science),2018,39(2):190-194
4 Smith R,Najarian K.Automated segmentation of pelvic bone structure in x-ray radiographs using active shape models and directed Hough transform[C]//IEEE International Conference on Bioinformatics and Biomeidcine Workshops.New York:IEEE,2008:56-63
5张婷,赵涓涓,罗嘉滢,等.基于多视觉深度信念网络的肺结节识别方法[J].科学技术与工程,2018,18(5):92-98Zhang Ting,Zhao Juanjuan,Luo Jiaying,et al.Pulmonary nodule detection method based on multi-view deep belief network[J].Science Technology and Engineering,2018,18(5):92-98
6 Li B,Lu H,Cai W,et al.Computer aided diagnosis and treatment planning for development dysplasis of the hip[J].Proceeding of SPIE-The International Society for Optical Engineering,2005,5744:781-788
7 Feng J,Won I S,Jeong J H,et al.Rigid and non-rigid object image matching using deformable object image discrimination[C]//Frontiers of Computer Vision.New York:IEEE,2015:1-4
8 Tavakoli V,Amini A A.A survey of shaped-based registration and segmentation techniques for cardiac images[J].Computer Vision&Image Understanding Cviu,2013,117(9):966-989
9 Nishihara S,Fujita H,Iida T,et al.Computer-aided diagnosis if osteoporosis using abdominal X-ray CT images:Preliminary study of automated region extraction and comparison between BMD values and CT features[J].Transactions of the Japanese Society for Medical&Biological Engineering Bme,2004,42:7-15
10 Terry Canale S,Beaty J H.坎贝尔骨科手术学[M].12版.王岩,译.北京:人民军医出版社.2013:172-174Terry Canale S.Beaty J H.Campbell’s operative orthopaedics[M].12th ed.Wang Yan,translated.Beijing:People’s Military Medical Press,2013:172-174