A novel method for spine ultrasound and X-ray radiograph registration

被引:1
作者
Jiang, Weiwei [1 ]
Xie, Qiaolin [1 ]
Qin, Yingyu [1 ]
Ye, Xiaojun [2 ]
Wang, Xiaoyan [1 ]
Zheng, Yongping [3 ]
机构
[1] Zhejiang Univ Technol, Coll Comp Sci & Technol, Hangzhou 310023, Peoples R China
[2] Hangzhou Womens Hosp, Dept Ultrasound, Hangzhou 310023, Peoples R China
[3] Hong Kong Polytech Univ, Dept Biomed Engn, Kowloon, Hong Kong, Peoples R China
关键词
Scoliosis imaging; Spine ultrasound; Registration; Mutual optimization; Mutual registration; IMAGE REGISTRATION; IDIOPATHIC SCOLIOSIS; 3-D ULTRASOUND; PREVALENCE; CURVATURE; SIFT; CT;
D O I
10.1016/j.ultras.2023.107018
中图分类号
O42 [声学];
学科分类号
070206 ; 082403 ;
摘要
Ultrasound is a promising imaging method for scoliosis evaluation because it is radiation free and provide real -time images. However, it cannot provide bony details because ultrasound cannot penetrate the bony structure. Therefore, registration of real-time ultrasound images with the previous X-ray radiograph can help physicians understand the spinal deformity of patients. In this study, an improved free-from deformation registration method based on mutual registration and hierarchical adaptive grid (MRHA-FFD) was developed. The method first performed registration grid preprocessing and then optimized control points and conducted mutual regis-tration. Finally, a Blur-aware Attention Network was adopted for image deblurring. The performance of each step was verified by ablation experiments. Comparison experiment between the proposed method and traditional registration methods was also conducted. The qualitative and quantitative results suggested that MRHA-FFD is a promising approach for registering spine ultrasound image and X-ray radiograph.
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页数:9
相关论文
共 45 条
  • [1] Medium-low resolution multisource remote sensing image registration based on SIFT and robust regional mutual information
    Chen, Shuhan
    Li, Xiaorun
    Zhao, Liaoying
    Yang, Han
    [J]. INTERNATIONAL JOURNAL OF REMOTE SENSING, 2018, 39 (10) : 3215 - 3242
  • [2] Reliability of assessing the coronal curvature of children with scoliosis by using ultrasound images
    Chen, Wei
    Lou, Edmond H. M.
    Zhang, Phoebe Q.
    Le, Lawrence H.
    Hill, Doug
    [J]. JOURNAL OF CHILDRENS ORTHOPAEDICS, 2013, 7 (06) : 521 - 529
  • [3] Freehand three-dimensional ultrasound system for assessment of scoliosis
    Cheung, Chung-Wai James
    Zhou, Guang-Quan
    Law, Siu-Yin
    Lai, Ka-Lee
    Jiang, Wei-Wei
    Zheng, Yong-Ping
    [J]. JOURNAL OF ORTHOPAEDIC TRANSLATION, 2015, 3 (03) : 123 - 133
  • [4] A deep learning framework for unsupervised affine and deformable image registration
    de Vos, Bob D.
    Berendsen, Floris F.
    Viergever, Max A.
    Sokooti, Hessam
    Staring, Marius
    Isgum, Ivana
    [J]. MEDICAL IMAGE ANALYSIS, 2019, 52 : 128 - 143
  • [5] Pulmonary CT Registration Through Supervised Learning With Convolutional Neural Networks
    Eppenhof, Koen A. J.
    Pluim, Josien P. W.
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2019, 38 (05) : 1097 - 1105
  • [6] Prevalence of Idiopathic Scoliosis in Chinese Schoolchildren A Large, Population-Based Study
    Fan Hengwei
    Huang Zifang
    Wang Qifei
    Tan Weiqing
    Deng Nali
    Yu Ping
    Yang Junlin
    [J]. SPINE, 2016, 41 (03) : 259 - 264
  • [7] A Meta-Analysis of the Clinical Effectiveness of School Scoliosis Screening
    Fong, Daniel Yee Tak
    Lee, Chun Fan
    Cheung, Kenneth Man Chee
    Cheng, Jack Chun Yiu
    Ng, Bobby Kin Wah
    Lam, Tsz Ping
    Mak, Kwok Hang
    Yip, Paul Siu Fai
    Luk, Keith Dip Kei
    [J]. SPINE, 2010, 35 (10) : 1061 - 1071
  • [8] LungRegNet: An unsupervised deformable image registration method for 4D-CT lung
    Fu, Yabo
    Lei, Yang
    Wang, Tonghe
    Higgins, Kristin
    Bradley, Jeffrey D.
    Curran, Walter J.
    Liu, Tian
    Yang, Xiaofeng
    [J]. MEDICAL PHYSICS, 2020, 47 (04) : 1763 - 1774
  • [9] An effective assessment method of spinal flexibility to predict the initial in-orthosis correction on the patients with adolescent idiopathic scoliosis (AIS)
    He, Chen
    To, Michael Kai-Tsun
    Cheung, Jason Pui-Yin
    Cheung, Kenneth Man-Chee
    Chan, Chi-Kwan
    Jiang, Wei-Wei
    Zhou, Guang-Quan
    Lai, Kelly Ka-Lee
    Zheng, Yong-Ping
    Wong, Man-Sang
    [J]. PLOS ONE, 2017, 12 (12):
  • [10] Horne JP, 2014, AM FAM PHYSICIAN, V89, P193