一种基于极大特征点的三维椎骨分割方法
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摘要
椎骨的精确分割对于椎骨形态学研究和脊柱疾病的诊断和治疗有重要意义。通过对正常人脊柱CT图序列的变化规律进行研究,提出了一种基于CT图像序列并利用椎骨面积变化规律进行分割的椎骨分割算法。该方法通过对预先处理后的CT图像序列进行椎骨区域面积统计,找出用于分割的显著极大特征点,并利用连续图像相似性筛选出椎骨实际分割点,最后从序列中提取图像并进行三维重建。实验表明,该算法对正常人体腰椎和胸椎下部的椎骨CT图像序列有良好地分割效果,自动化程度较高。对脊柱形态学研究和矫正手术模拟有重要意义。
Accurate segmentation of vertebrae has become more and more important for the diagnosis and treatment of spinal diseases. After studying the change rule of some spinal CT image sequences of normal people, we proposed a new vertebral segmentation algorithm based on vertebral area change regulation. This method first calculates the area of vertebral region in the image after pre-processing, then finds out the significant features for segmentation, uses image similarity of continuous images to select the actual segmentation points, and finally extracts vertebral images from image sequence for 3 D reconstruction. The innovation of the method is that a new segmentation algorithm based on the maximum feature and correlation of CT image sequence is proposed. The experimental results show that the algorithm has a good segmentation effect on the CT image sequence of lumbar vertebrae and the lower thoracic vertebrae of normal human bodies and it has a high degree of automation. This study is of great significance to the morphological study of the spine and the simulation of the scoliosis operation.
Accurate segmentation of vertebrae has become more and more important for the diagnosis and treatment of spinal diseases. After studying the change rule of some spinal CT image sequences of normal people, we proposed a new vertebral segmentation algorithm based on vertebral area change regulation. This method first calculates the area of vertebral region in the image after pre-processing, then finds out the significant features for segmentation, uses image similarity of continuous images to select the actual segmentation points, and finally extracts vertebral images from image sequence for 3 D reconstruction. The innovation of the method is that a new segmentation algorithm based on the maximum feature and correlation of CT image sequence is proposed. The experimental results show that the algorithm has a good segmentation effect on the CT image sequence of lumbar vertebrae and the lower thoracic vertebrae of normal human bodies and it has a high degree of automation. This study is of great significance to the morphological study of the spine and the simulation of the scoliosis operation.
引文
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[2]ZHAO L K,ZHENG S Y,WEI H T.Adaptive active contour model driven by global and local intensity fitting energy for image segmentation[J].OptikInternational Journal for Light and Electron Optics,2017,140:908-920.
[3]COURBOT J B,RUST E,Monfrini E.Vertebra segmentation based on two-step refinement[J].Journal of Computational Surgery,2016,4(1):1.
[4]KIM Y,KIM D.A fully automatic vertebra segmentation method using 3D deformable fences[J].Computerized Medical Imaging and Graphics:the Official Journal of the Computerized Medical Imaging Society,2009,33(5):343-352.
[5]ATHERTYA J S,SARAVANA K G.Automatic segmentation of vertebral contours from CT images using fuzzy corners[J].Computers in Biology and Medicine,2016,72:75-89.
[6]CHENG E K,LIU Y X,WIBOWO H,et al.Learning-based spine vertebra localization and segmentation in 3D CT image[C]//IEEE 13th International Symposium on Biomedical Imaging(ISBI2016).New York:IEEE Press,2016:160-163.
[7]SUZANI A,RASOULIAN A,SEITEL A.Deep learning for automatic localization,identification,and segmentation of vertebral bodies in volumetric MR images[EB/OL].(2015-03-18)[2018-06-29].https://doi.org/10.1117/12.2081542.
[8]RASOULIAN A,ROHLING R,ABOLMAESUMI P.Lumbar spine segmentation using a statistical multi-vertebrae anatomical Shape+Pose model[J].IEEE Transactions on Medical Imaging,2013,32(10):1890-1900.
[9]KOREZ R,IBRAGIMOV B,LIKAR B.A Framework for automated spine and vertebrae interpolation-based detection and model-based segmentation[J].IEEETransactions on Medical Imaging,2015,34(8):1649-1662.
[10]LI C,MANTELL S,POLLA D.Design and simulation of an implantable medical drug delivery system using microelectro-mechanical systems technology[J].Sensors and Actuators A Physical,2001,94(1):117-125.
[11]ESCOTT E J,RUBINSTEIN D.Free DICOM image viewing and processing software for your desktop computer:What’s available and what it can do for you[J].Radiographics,2003,23(5):1341-1357.
[12]ROSSET A,SPADOLA L,RATIB O.OsiriX:An open-source software for navigating in multidimensional DICOM images[J].Journal of Digital Imaging,2004,17(3):205-216.
[13]CHUNG H COBXAS D,BIRDSELL L,et al.Automated segmentation of muscle and adipose tissue on CT images for human body composition analysis[C]//Medical Imaging 2009:Visualization,Image-Guided Procedures,and Modeling.Bellingham:International Society for Optics and Photonics,2009:72610K-72610K-8.
[14]姚沛延,赵宏安,周明全,等.基于CT图像的脊椎骨组织分割[J].计算机工程与应用,2009,45(27):237-239.