A low-cost tracked C-arm (TC-arm) upgrade system for versatile quantitative intraoperative imaging

  • Shahram AmiriEmail author
  • David R. Wilson
  • Bassam A. Masri
  • Carolyn Anglin
Original Article



   C-arm fluoroscopy is frequently used in clinical applications as a low-cost and mobile real-time qualitative assessment tool. C-arms, however, are not widely accepted for applications involving quantitative assessments, mainly due to the lack of reliable and low-cost position tracking methods, as well as adequate calibration and registration techniques. The solution suggested in this work is a tracked C-arm (TC-arm) which employs a low-cost sensor tracking module that can be retrofitted to any conventional C-arm for tracking the individual joints of the device.


   Registration and offline calibration methods were developed that allow accurate tracking of the gantry and determination of the exact intrinsic and extrinsic parameters of the imaging system for any acquired fluoroscopic image. The performance of the system was evaluated in comparison to an Optotrak\(^\mathrm{TM}\) motion tracking system and by a series of experiments on accurately built ball-bearing phantoms. Accuracies of the system were determined for 2D–3D registration, three-dimensional landmark localization, and for generating panoramic stitched views in simulated intraoperative applications.


   The system was able to track the center point of the gantry with an accuracy of \(1.5 \pm 1.2\) mm or better. Accuracies of 2D–3D registrations were \(2.3 \pm 1.1\) mm and \(0.2 \pm 0.2^{\circ }\). Three-dimensional landmark localization had an accuracy of \(3.1 \pm 1.3\%\) of the length (or \(4.4 \pm 1.9\) mm) on average, depending on whether the landmarks were located along, above, or across the table. The overall accuracies of the two-dimensional measurements conducted on stitched panoramic images of the femur and lumbar spine were 2.5 \(\pm \) 2.0 % \((3.1 \pm 2.5 \hbox { mm})\) and \(0.3 \pm 0.2^{\circ }\), respectively.


   The TC-arm system has the potential to achieve sophisticated quantitative fluoroscopy assessment capabilities using an existing C-arm imaging system. This technology may be useful to improve the quality of orthopedic surgery and interventional radiology.


Quantitative C-arm Multi-planar radiography Tracked C-arm  TC-arm Image stitching C-arm fluoroscopy 



This work is supported by funding from the Canadian Arthritis Network - Discovery Advancement Program (CAN-DAP), Orthopaedics Research Excellence Fund (OREF) from the University of British Columbia, Alberta Innovates Technology Futures, and NSERC Discovery Grant.

Conflict of interest

The authors confirm that there are no known conflicts of interest associated with this publication.


  1. 1.
    Hofstetter R, Slomczykowski M, Sati M (1999) Fluoroscopy as an imaging means for computer-assisted surgical navigation. Comput Aid Surg 4(2):65–76CrossRefGoogle Scholar
  2. 2.
    Jain A, Deguet A, Iordachita I, Chintalapani G, Blevins J, Le Y, Armour E, Burdette C, Song D, Fichtinger G (2007) Intra-operative 3D guidance in prostate brachytherapy using a non-isocentric C-arm. Med Image Comput Comput Assist Interv MICCAI 10(Pt 2): 9–17Google Scholar
  3. 3.
    Hofstetter R, Slomczykowski M, Krettek C, Koppen G, Sati M, Nolte LP (2000) Computer-assisted fluoroscopy-based reduction of femoral fractures and antetorsion correction. Comput Aid Surg 5(5):311–325. doi: 10.1002/1097-0150(2000)5:5<311:Aid-Igs1>3.0.Co;2-J
  4. 4.
    Collinge C, Coons D, Tornetta P, Aschenbrenner J (2005) Standard multiplanar fluoroscopy versus a fluoroscopically based navigation system for the percutaneous insertion of iliosacral screws: a cadaver model. J Orthop Trauma 19(4):254–258PubMedCrossRefGoogle Scholar
  5. 5.
    Foley KT, Simon DA, Rampersaud YR (2001) Virtual fluoroscopy: computer-assisted fluoroscopic navigation. Spine 26(4):347–351Google Scholar
  6. 6.
    Suhm N, Messmer P, Zuna I, Regazzoni P (2004) Fluoroscopic guidance versus surgical navigation for distal locking of intramedullary implants. Injury 35(6):567–574. doi: 10.1016/S0020-1383(03)00312-7 PubMedCrossRefGoogle Scholar
  7. 7.
    Chen X, Wang L, Fallavollita P, Navab N (2013) Precise X-ray and video overlay for augmented reality fluoroscopy. Int J Comput Assist Radiol Surg 8(1):29–38. doi: 10.1007/S11548-012-0746-X PubMedCrossRefGoogle Scholar
  8. 8.
    Binder N, Matthaus L, Burgkart R, Schweikard A (2005) A robotic C-arm fluoroscope. Int J Med Robot Comput Assist Surg MRCAS 1(3):108–116. doi: 10.1002/Rcs.34 Google Scholar
  9. 9.
    Finke M, Bruder R, Schweikard A (2008) Kinematics of a robotized operation microscope. IEEE Industrial Electronics, pp 1579–1584Google Scholar
  10. 10.
    Amiri S, Masri BA, Garbuz D, Anglin C, Wilson DR (2012) A multiplanar radiography method for assessing cup orientation in total hip arthroplasty. J Biomech Eng 134(10):101008. doi: 10.1115/1.4007664 Google Scholar
  11. 11.
    Amiri S, Wilson DR, Masri BA, Sharma G, Anglin C (2011) A novel multi-planar radiography method for three dimensional pose reconstruction of the patellofemoral and tibiofemoral joints after arthroplasty. J Biomech 44(9):1757–1764. doi: 10.1016/J.Jbiomech.2011.04.006 Google Scholar
  12. 12.
    Amiri S, Anglin C, Agbanlog K, Masri BA, Wilson DR (2012) A model-free feature-based bi-planar RSA method for kinematic analysis of total knee arthroplasty. J Biomech Eng 134(3):031009. doi: 10.1115/1.4006198 Google Scholar
  13. 13.
    Amiri S, Masri BA, Anglin C, Wilson DR (2013) A method for assessing joint line shift post knee arthroplasty considering the preoperative joint space. The Knee (in press). doi: 10.1016/J.Knee.2013.03.011
  14. 14.
    Yaniv Z, Joskowicz L (2004) Long bone panoramas from fluoroscopic X-ray images. IEEE Trans Med Imaging 23(1):26–35. doi: 10.1109/Tmi.2003.819931 PubMedCrossRefGoogle Scholar
  15. 15.
    Wang L, Traub J, Heining SM, Benhimane S, Euler E, Graumann R, Navab N (2008) Long bone X-ray image stitching using camera augmented mobile C-arm. Med Image Comput Comput Assist Interv MICCAI 11(2):578–586Google Scholar
  16. 16.
    Wang L, Traub J, Weidert S, Euler E, Navab N (2010) Parallax-free intra-operative X-ray image stitching. Med Image Anal 14(5):674–686. doi: 10.1016/J.Media.2010.05.007 PubMedCrossRefGoogle Scholar
  17. 17.
    Jenny JY, Boeri C, Picard F, Leitner F (2004) Reproducibility of intra-operative measurement of the mechanical axes of the lower limb during total knee replacement with a non-image-based navigation system. Comput Aid Surg 9(4):161–165. doi: 10.3109/10929080500095517
  18. 18.
    Bassi S, Baldini S, Rebuffat C, Sarti R, Ferretti F (2013) First test on three stitching methods with digital detectors used in radiography. Radiol Phys Technol 6(1):187–196. doi: 10.1007/S12194-012-0187-9 PubMedCrossRefGoogle Scholar
  19. 19.
    Reaungamornrat S, Otake Y, Uneri A, Schafer S, Nithiananthan S, Kleinszig G, Taylor RH, Siewerdsen JH (2012) An on-board surgical tracking and video augmentation system for C-arm image guidance. Int J Comput Assist Radiol Surg 7(5):647–665. doi: 10.1007/S11548-012-0682-9 Google Scholar
  20. 20.
    Reaungamornrat S, Otake Y, Uneri A, Schafer S, Stayman J, Zbijewski W, Mirota D, Yoo J, Nithiananthan S, Khanna A (2011) Tracker-on-C: a novel tracker configuration for image-guided therapy using a mobile C-arm. Computer assisted radiology and surgery. Berlin, Germany, pp 22–25Google Scholar
  21. 21.
    Bo LE, Leira HO, Tangen GA, Hofstad EF (2012) Accuracy of electromagnetic tracking with a prototype field generator in an interventional OR setting. Med Phys 39(1):399–406. doi: 10.1118/1.3666768 Google Scholar
  22. 22.
    Hummel J, Figl M, Birkfellner W, Bax Mr, Shahidi R, Maurer CR Jr, Bergmann H (2006) Evaluation of a new electromagnetic tracking system using a standardized assessment protocol. Phys Med Biol 51(10):N205–N210PubMedCrossRefGoogle Scholar
  23. 23.
    Grzeda V, Fichtinger G (2010) C-arm rotation encoding with accelerometers. Int J Comput Assist Radiol Surg 5(4):385–391. doi: 10.1007/S11548-010-0415-X PubMedCrossRefGoogle Scholar
  24. 24.
    Grzeda V, Fichtinger G (2010) Rotational encoding of C-arm fluoroscope with tilt sensing accelerometer. Lect Notes Comput Sci 6363:424–431CrossRefGoogle Scholar
  25. 25.
    Idler C, Rolfe KW, Gorek JE (2010) Accuracy of percutaneous lumbar pedicle screw placement using the oblique or ”owl’s-eye” view and novel guidance technology. J Neurosurg Spine 13(4):509–515. doi: 10.3171/2010.4.Spine09580
  26. 26.
    Yang BP, Wahl MM, Idler CS (2012) Percutaneous lumbar pedicle screw placement aided by computer-assisted fluoroscopy-based navigation: perioperative results of a prospective, comparative multicenter study. Spine 37(24):2055–2060. doi: 10.1097/Brs.0b013e31825c05cd Google Scholar
  27. 27.
    Livyatan H, Yaniv Z, Joskowicz L (2002) Robust automatic C-arm calibration for fluoroscopy-based navigation: a practical approach. In: Dohi T, Kikinis R (eds) Medical image computing and computer-assisted intervention—Miccai 2002, vol 2489, Lecture notes in computer science. Springer, Berlin Heidelberg, pp 60–68. doi: 10.1007/3-540-45787-9_8
  28. 28.
    Burkhardt D, Jain A, Fichtinger G (2007) A cheap and easy method for 3D C-arm reconstruction using elliptic curves. In: Proceedings of the SPIE 6509. doi:Artn 65090b doi: 10.1117/12.712395
  29. 29.
    Chintalapani G, Jain AK, Burkhardt DH, Prince JL, Fichtinger G (2008) CTREC: C-arm tracking and reconstruction using elliptic curves. In: Proceedings of the CVPR IEEE, pp 596– 602Google Scholar
  30. 30.
    Ayad MS, Lee J, Deguet A, Burdette EC, Prince JL (2010) C-arm pose estimation using a set of coplanar ellipses in correspondence. In: Proceedings/IEEE international symposium on biomedical imaging: from nano to macro IEEE international symposium on biomedical imaging 2010, pp 1401–1404. doi: 10.1109/Isbi.2010.5490260
  31. 31.
    Cho Y, Moseley DJ, Jaffray DA (2005) Accurate technique for complete geometric calibration of cone-beam computed tomography systems. Med Phys 32(4):968–983Google Scholar
  32. 32.
    Daly MJ, Siewerdsen JH (2008) Geometric calibration of a mobile C-arm for intraoperative cone-beam CT. Med Phys 35(5):2124–2136Google Scholar
  33. 33.
    Lewinnek GE, Lewis JL, Compere CL, Zimmerman JR (1978) Dislocations after total hip-replacement arthroplasties. J Bone Jt Surg Am 60(2):217–220Google Scholar
  34. 34.
    Dehghan E, Jain AK, Morris WJ, Salcudean SE (2011) Brachytherapy seed reconstruction with joint-encoded C-arm single-axis rotation and motion compensation. Med Image Anal 15(5):760–771. doi: 10.1016/J.Media.2011.05.017 Google Scholar
  35. 35.
    Dehghan E, Lee J, Moradi M, Wen X, Fichtinger G (2010) Prostate brachytherapy seed reconstruction using C-arm rotation measurement and motion compensation. Med Image Comput Comput Assist Interv MICCAI 13(Pt 1):283–290Google Scholar
  36. 36.
    Dehghan E, Moradi M, Wen X, French D, Lobo J, Fichtinger G (2011) Prostate implant reconstruction from C-arm images with motion-compensated tomosynthesis. Med Phys 38(10):5290–5302. doi: 10.1118/1.3633897 PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© CARS 2013

Authors and Affiliations

  • Shahram Amiri
    • 1
    • 2
    Email author
  • David R. Wilson
    • 1
    • 2
  • Bassam A. Masri
    • 1
  • Carolyn Anglin
    • 3
  1. 1.Department of OrthopaedicsUniversity of British ColumbiaVancouverCanada
  2. 2.Centre for Hip Health and Mobility (CHHM)Robert H.N. Ho Research CentreVancouverCanada
  3. 3.Biomedical Engineering, Department of Civil Engineering, McCaig Institute for Bone and Joint HealthUniversity of CalgaryCalgaryCanada

Personalised recommendations