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An automatic measurement method of spinal curvature on ultrasound coronal images in adolescent idiopathic scoliosis

1 College of Computer Science & Technology, Zhejiang University of Technology, Hangzhou 310014, China
2 State Key Laboratory of Bioelectronics, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China
3 Interdisciplinary Division of Biomedical Engineering, The Hong Kong Polytechnic University, Kowloon, Hong Kong 999077, China
4 School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China

Special Issues: Advanced Computer Methods and Programs in Biomedicine

This study proposed a new automatic measurement method of spinal curvature on ultrasound coronal images in adolescent idiopathic scoliosis (AIS). After preprocessing of Gaussian enhancement, the symmetric information of the image was extracted using the phase congruency. Then bony features were segmented from the soft tissues and background using the greyscale polarity. The morphological methods of image erosion and top-bottom-hat transformation, and geometric moment were utilized to identify the spinous column profile from the transverse processes. Finally, the spine deformity curve was obtained using robust regression. In-vivo experiments based on AIS patients were performed to evaluate the performance of the developed method. The comparison results revealed there was a significant correlation (y=0.81x, r=0.86) and good agreement between the new automatic method and the manual measurement method. It can be expected that this novel method may help to provide effective and objective deformity assessment method during the ultrasound scanning for AIS patients.
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Keywords automatic measurement; scoliosis; ultrasound; segmentation; phase congruency

Citation: Wei-wei Jiang, Xin-xin Zhong, Guang-quan Zhou, Qiu Guan, Yong-ping Zheng, Sheng-yong Chen. An automatic measurement method of spinal curvature on ultrasound coronal images in adolescent idiopathic scoliosis. Mathematical Biosciences and Engineering, 2020, 17(1): 776-788. doi: 10.3934/mbe.2020040


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