Automatic Measurement of Spine Curvature on 3-D Ultrasound Volume Projection Image With Phase Features

This paper presents an automated measurement of spine curvature by using prior knowledge on vertebral anatomical structures in ultrasound volume projection imaging (VPI). This method can be used in scoliosis assessment with free-hand 3-D ultrasound imaging. It is based on the extraction of bony features from VPI images using a newly proposed two-fold thresholding strategy, with information of the symmetric and asymmetric measures obtained from phase congruency. The spinous column profile is detected from the segmented bony regions, and it is further used to extract a curve representing spine profile. The spine curvature is then automatically calculated according to the inflection points along the curve. The algorithm was evaluated on volunteers with the different severity of scoliosis. The results obtained using the newly developed method had a good linear correlation with those by the manual method (<inline-formula> <tex-math notation="LaTeX">${r} \ge 0.90$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${p} < 0.001$ </tex-math></inline-formula>) and X-ray Cobb’s method (<inline-formula> <tex-math notation="LaTeX">${r} =0.83$ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">${p} < 0.001$ </tex-math></inline-formula>). The bigger variations observed in the manual measurement also implied that the automatic method is more reliable. The proposed method can be a promising approach for facilitating the applications of 3-D ultrasound imaging in the diagnosis, treatment, and screening of scoliosis.

[1]  Cobb,et al.  Outlines for the study of scoliosis , 1948 .

[2]  N. Otsu A threshold selection method from gray level histograms , 1979 .

[3]  Andrew K. C. Wong,et al.  A new method for gray-level picture thresholding using the entropy of the histogram , 1985, Comput. Vis. Graph. Image Process..

[4]  W. P. Bunnell,et al.  The Natural History of Idiopathic Scoliosis Before Skeletal Maturity , 1986, Spine.

[5]  J M Bland,et al.  Statistical methods for assessing agreement between two methods of clinical measurement , 1986 .

[6]  Robyn A. Owens,et al.  Feature detection from local energy , 1987, Pattern Recognit. Lett..

[7]  T Yamamuro,et al.  Ultrasound measurement of vertebral rotation in idiopathic scoliosis. , 1989, The Journal of bone and joint surgery. British volume.

[8]  J. Boice,et al.  Breast cancer in women with scoliosis exposed to multiple diagnostic x rays. , 1989, Journal of the National Cancer Institute.

[9]  E. Hall,et al.  Measurement of the Cobb angle on radiographs of patients who have scoliosis. Evaluation of intrinsic error. , 1990, The Journal of bone and joint surgery. American volume.

[10]  A B Schultz,et al.  Cobb Angle Versus Spinous Process Angle in Adolescent Idiopathic Scoliosis The Relationship of the Anterior and Posterior Deformities , 1990, Spine.

[11]  J. Birch,et al.  Measurement of scoliosis and kyphosis radiographs. Intraobserver and interobserver variation. , 1990, The Journal of bone and joint surgery. American volume.

[12]  John C. Russ,et al.  The Image Processing Handbook , 2016, Microscopy and Microanalysis.

[13]  M. J. Stokes,et al.  Pattern of asymmetry of paraspinal muscle size in adolescent idiopathic scoliosis examined by real-time ultrasound imaging. A preliminary study. , 1993, Spine.

[14]  Adrian R. Levy,et al.  REDUCING THE LIFETIME RISK OF CANCER FROM SPINAL RADIOGRAPHS AMONG PEOPLE WITH ADOLESCENT IDIOPATHIC SCOLIOSIS , 1997 .

[15]  Peter Kovesi,et al.  Symmetry and Asymmetry from Local Phase , 1997 .

[16]  Barthold Lichtenbelt,et al.  Introduction to volume rendering , 1998 .

[17]  P Kovesi,et al.  Phase congruency: A low-level image invariant , 2000, Psychological research.

[18]  Marilyn Stovall,et al.  Breast Cancer Mortality After Diagnostic Radiography: Findings From the U.S. Scoliosis Cohort Study , 2000, Spine.

[19]  Michael Felsberg,et al.  The monogenic signal , 2001, IEEE Trans. Signal Process..

[20]  Bülent Sankur,et al.  Survey over image thresholding techniques and quantitative performance evaluation , 2004, J. Electronic Imaging.

[21]  Chih-Chin Lai,et al.  A Hybrid Approach Using Gaussian Smoothing and Genetic Algorithm for Multilevel Thresholding , 2004, Int. J. Hybrid Intell. Syst..

[22]  J. Pruijs,et al.  Variation in Cobb angle measurements in scoliosis , 1994, Skeletal Radiology.

[23]  Marilyn Stovall,et al.  Multiple Diagnostic X-rays for Spine Deformities and Risk of Breast Cancer , 2008, Cancer Epidemiology Biomarkers & Prevention.

[24]  Joachim Hornegger,et al.  Computer-Aided Assessment of Anomalies in the Scoliotic Spine in 3-D MRI Images , 2009, MICCAI.

[25]  Ahror Belaid,et al.  Phase based level set segmentation of ultrasound images , 2009, 2009 9th International Conference on Information Technology and Applications in Biomedicine.

[26]  Antony J Hodgson,et al.  Bone surface localization in ultrasound using image phase-based features. , 2009, Ultrasound in medicine & biology.

[27]  Chung-Wai James Cheung,et al.  Development of 3-D Ultrasound System for Assessment of Adolescent Idiopathic Scoliosis (AIS) , 2010 .

[28]  Peter M A van Ooijen,et al.  A framework for human spine imaging using a freehand 3D ultrasound system. , 2010, Technology and health care : official journal of the European Society for Engineering and Medicine.

[29]  Raymond Y. W. Lee,et al.  Biplanar measurement of thoracolumbar curvature in older adults using an electromagnetic tracking device. , 2010, Archives of physical medicine and rehabilitation.

[30]  Jin-Suck Suh,et al.  Scoliosis imaging: what radiologists should know. , 2010, Radiographics : a review publication of the Radiological Society of North America, Inc.

[31]  Patrick Siarry,et al.  A comparative study of various meta-heuristic techniques applied to the multilevel thresholding problem , 2010, Eng. Appl. Artif. Intell..

[32]  Cameron Walker,et al.  Spinous process morphology: the effect of ageing through adulthood on spinous process size and relationship to sagittal alignment , 2012, European Spine Journal.

[33]  Wei Chen,et al.  Using ultrasound imaging to identify landmarks in vertebra models to assess spinal deformity , 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[34]  Jiri Salinger,et al.  Optimization of the examination posture in spinal curvature assessment , 2012, Scoliosis.

[35]  Antony J Hodgson,et al.  Automatic bone localization and fracture detection from volumetric ultrasound images using 3-D local phase features. , 2012, Ultrasound in medicine & biology.

[36]  Yong-Ping Zheng,et al.  Development of 3-D ultrasound system for assessment of adolescent idiopathic scoliosis (AIS): And system validation , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[37]  M. Wybier,et al.  Musculoskeletal imaging in progress: the EOS imaging system. , 2013, Joint, bone, spine : revue du rhumatisme.

[38]  Doug Hill,et al.  Reliability of assessing the coronal curvature of children with scoliosis by using ultrasound images , 2013, Journal of children's orthopaedics.

[39]  G. J. Verkerke,et al.  Automatic Cobb Angle Determination From Radiographic Images , 2013, Spine.

[40]  Rüdiger Krauspe,et al.  Epidemiology of adolescent idiopathic scoliosis , 2013, Journal of children's orthopaedics.

[41]  Saif Usman,et al.  Adolescent idiopathic scoliosis: diagnosis and management. , 2014, American family physician.

[42]  Andras Lasso,et al.  Spinal curvature measurement by tracked ultrasound snapshots. , 2014, Ultrasound in medicine & biology.

[43]  Purang Abolmaesumi,et al.  Local Phase Tensor Features for 3-D Ultrasound to Statistical Shape+Pose Spine Model Registration , 2014, IEEE Transactions on Medical Imaging.

[44]  Jing-Yi Guo,et al.  Assessment of scoliotic deformity using spinous processes: comparison of different analysis methods of an ultrasonographic system. , 2014, Journal of manipulative and physiological therapeutics.

[45]  Antony J Hodgson,et al.  Volume‐specific parameter optimization of 3D local phase features for improved extraction of bone surfaces in ultrasound , 2014, The international journal of medical robotics + computer assisted surgery : MRCAS.

[46]  Vipin Chaudhary,et al.  Vertebral Column Localization, Labeling, and Segmentation , 2015 .

[47]  Purang Abolmaesumi,et al.  Bone enhancement in ultrasound using local spectrum variations for guiding percutaneous scaphoid fracture fixation procedures , 2015, International Journal of Computer Assisted Radiology and Surgery.

[48]  Rui Zheng,et al.  Reliability and accuracy of ultrasound measurements with and without the aid of previous radiographs in adolescent idiopathic scoliosis (AIS) , 2015, European Spine Journal.

[49]  Guang-Quan Zhou,et al.  Freehand three-dimensional ultrasound system for assessment of scoliosis , 2015, Journal of orthopaedic translation.

[50]  Yong-Ping Zheng,et al.  Assessment of scoliosis using 3-D ultrasound volume projection imaging with automatic spine curvature detection , 2015, 2015 IEEE International Ultrasonics Symposium (IUS).

[51]  Yong-Ping Zheng,et al.  Ultrasound Volume Projection Imaging for Assessment of Scoliosis , 2015, IEEE Transactions on Medical Imaging.

[52]  Edmond Lou,et al.  3D ultrasound imaging method to assess the true spinal deformity , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[53]  M. D. Sèze,et al.  Patient-specific 3D models created by 3D imaging system or bi-planar imaging coupled with Moiré–Fringe projections: a comparative study of accuracy and reliability on spinal curvatures and vertebral rotation data , 2016, European Spine Journal.

[54]  Jack C. Y. Cheng,et al.  Radiation dose of digital radiography (DR) versus micro-dose x-ray (EOS) on patients with adolescent idiopathic scoliosis: 2016 SOSORT- IRSSD “John Sevastic Award” Winner in Imaging Research , 2016, Scoliosis and Spinal Disorders.

[55]  Guang-Quan Zhou,et al.  A reliability and validity study for Scolioscan: a radiation-free scoliosis assessment system using 3D ultrasound imaging , 2016, Scoliosis and Spinal Disorders.