Image-based RSA: Roentgen stereophotogrammetric analysis based on 2D-3D image registration

被引:36
|
作者
de Bruin, P. W. [1 ,2 ]
Kaptein, B. L. [1 ]
Stoel, B. C. [2 ]
Reiber, J. H. C. [2 ]
Rozing, P. M. [1 ]
Valstar, E. R. [1 ]
机构
[1] Leiden Univ, Med Ctr, Dept Orthopaed, Leiden, Netherlands
[2] Leiden Univ, Med Ctr, Dept Radiol, Div Image Proc, Leiden, Netherlands
关键词
roentgen stereophotogrammetric analysis; RSA; 2D-3D registration; image-based RSA;
D O I
10.1016/j.jbiomech.2007.07.002
中图分类号
Q6 [生物物理学];
学科分类号
071011 ;
摘要
Image-based Roentgen stereophotogrammetric analysis (IBRSA) integrates 2D-3D image registration and conventional RSA. Instead of radiopaque RSA bone markers, IBRSA uses 3D CT data, from which digitally reconstructed radiographs (DRRs) are generated. Using 2D-3D image registration, the 3D pose of the CT is iteratively adjusted such that the generated DRRs resemble the 2D RSA images as closely as possible, according to an image matching metric. Effectively, by registering all 2D follow-up moments to the same 3D CT, the CT volume functions as common ground. In two experiments, using RSA and using a micromanipulator as gold standard, IBRSA has been validated on cadaveric and sawbone scapula radiographs, and good matching results have been achieved. The accuracy was: vertical bar mu vertical bar <0.083 mm for translations and vertical bar mu vertical bar < 0.023 degrees for rotations. The precision a in x-, y-, and z-direction was 0.090, 0.077, and 0.220 mm for translations and 0.155 degrees, 0.243 degrees, and 0.074 degrees for rotations. Our results show that the accuracy and precision of in vitro IBRSA, performed under ideal laboratory conditions, are lower than in vitro standard RSA but higher than in vivo standard RSA. Because IBRSA does not require radiopaque markers, it adds functionality to the RSA method by opening new directions and possibilities for research, such as dynamic analyses using fluoroscopy on subjects without markers and computer navigation applications. (c) 2007 Elsevier Ltd. All rights reserved.
引用
收藏
页码:155 / 164
页数:10
相关论文
共 50 条
  • [1] Multilevel 2D-3D Intensity-Based Image Registration
    Lange, Annkristin
    Heldmann, Stefan
    [J]. BIOMEDICAL IMAGE REGISTRATION (WBIR 2020), 2020, 12120 : 57 - 66
  • [2] 2D-3D Medical image registration based on ant colony algorithm
    Wei, Wei
    Lin, Wei
    Liu, Liang
    Hu, Zhongqin
    [J]. PROGRESS IN MECHATRONICS AND INFORMATION TECHNOLOGY, PTS 1 AND 2, 2014, 462-463 : 267 - +
  • [3] OpenGL based 2D-3D registration of a CT image dataset with OBI images
    Choi, B.
    Balter, P.
    Dong, L.
    Mohan, R.
    Starkschall, G.
    [J]. MEDICAL PHYSICS, 2006, 33 (06) : 2161 - 2161
  • [4] A Neural Network Based Registration Quality Evaluator for 2D-3D Image Registrations
    Wu, J.
    Murphy, M.
    Samant, S.
    [J]. MEDICAL PHYSICS, 2010, 37 (06)
  • [5] A robust image-based method for 3D registration
    Li, T
    [J]. FIFTH INTERNATIONAL CONFERENCE ON 3-D DIGITAL IMAGING AND MODELING, PROCEEDINGS, 2005, : 270 - 276
  • [6] An Open Platform for 2D-3D Image Registration Experiments
    Balter, J.
    Long, Y.
    Folkerts, M.
    Sharp, G.
    Bortfeld, T.
    Fessler, J.
    [J]. MEDICAL PHYSICS, 2011, 38 (06)
  • [7] A Computationally Efficient Approach for 2D-3D Image Registration
    Haque, Md. Nazmul
    Pickering, Mark R.
    Biswas, Moyuresh
    Frater, Michael R.
    Scarvell, Jennie M.
    Smith, Paul N.
    [J]. 2010 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2010, : 6268 - 6271
  • [8] FULLY AUTOMATED INITIALISATION OF 2D-3D IMAGE REGISTRATION
    Varnavas, Andreas
    Carrell, Tom
    Penney, Graeme
    [J]. 2013 IEEE 10TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI), 2013, : 568 - 571
  • [9] Similarity metrics based on nonadditive entropies for 2D-3D multimodal biomedical image registration
    Wachowiak, MP
    Smolilcova, R
    Tourassi, GD
    Elmaghraby, AS
    [J]. MEDICAL IMAGING 2003: IMAGE PROCESSING, PTS 1-3, 2003, 5032 : 1090 - 1100
  • [10] 2D-3D Medical Image Registration Based on Training-Inference Decoupling Architecture
    Li Wenju
    Kong Deqing
    Cao Guogang
    Li Sicheng
    Dai Cuixia
    [J]. LASER & OPTOELECTRONICS PROGRESS, 2022, 59 (16)