C-arm rotation encoding with accelerometers

Original Article



Fluoroscopic C-arms are being incorporated in computer-assisted interventions in increasing number. For these applications to work, the relative poses of imaging must be known. To find the pose, tracking methods such as optical cameras, electromagnetic trackers, and radiographic fiducials have been used—all hampered by significant shortcomings.


We propose to recover the rotational pose of the C-arm using the angle-sensing ability of accelerometers, by exploiting the capability of the accelerometer to measure tilt angles. By affixing the accelerometer to a C-arm, the accelerometer tracks the C-arm pose during rotations of the C-arm. To demonstrate this concept, a C-arm analogue was constructed with a webcam device affixed to the C-arm model to mimic X-ray imaging. Then, measuring the offset between the accelerometer angle readings to the webcam pose angle, an angle correction equation (ACE) was created to properly tracking the C-arm rotational pose.

Experiments and results

Several tests were performed on the webcam C-arm model using the ACEs to tracking the primary and secondary angle rotations of the model. We evaluated the capability of linear and polynomial ACEs to tracking the webcam C-arm pose angle for different rotational scenarios. The test results showed that the accelerometer could track the pose of the webcam C-arm model with an accuracy of less than 1.0 degree.


The accelerometer was successful in sensing the C-arm’s rotation with clinically adequate accuracy in the C-arm webcam model.


C-arm Encoding Accelerometer 


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  1. 1.
    Barshan B, Durrant-Whyte HF (1995) Inertial navigation system for mobile robots. IEEE Trans Robotics Automation 11(2): 328–345CrossRefGoogle Scholar
  2. 2.
    Batista J, Araujo H, Almeida AT (1996) Pose view stability analysis for camera look angles computation. In: Proceeding of the 13th international conference on pattern recognition (ICPR), pp 171–175Google Scholar
  3. 3.
    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 10(Pt 2): 9–17PubMedGoogle Scholar
  4. 4.
    Jain A, Fichtinger G (2006) C-arm tracking and reconstruction without an external tracker. Med Image Comput Comput Assist Interv 9(Pt 1): 494–502CrossRefPubMedGoogle Scholar
  5. 5.
    Jain A, Mustafa T, Zhou Y, Burdette C, Chirikjian GS, Fichtinger G (2006) FTRAC—A robust fluoroscope tracking fiducial. Med Phys 32(10): 3185–3198CrossRefGoogle Scholar
  6. 6.
    Lee J, Liu X, Jain AK, Song DY, Burdette EC, Prince JL, Fichtinger G (2009) Prostate brachytherapy seed reconstruction with Gaussian blurring and optimal coverage cost. IEEE Trans Med Imaging 28(12): 1955–1968CrossRefPubMedGoogle Scholar
  7. 7.
    Peters T, Cleary K (eds) (2008) In: Image-guided interventions: technology and applications, SpringerGoogle Scholar
  8. 8.
    Nikbakht S, Mazlom M, Khayatian A (2005) Evaluation of solid-state accelerometer for positioning of vehicle. In: IEEE internatonal conference on industrial technology (ICIT), pp 729–733Google Scholar
  9. 9.
    Tan CW, Park S (2005) Design of accelerometer-based inertial navigation system. IEEE Trans Instrum Measurement 54(6): 2520–2530CrossRefGoogle Scholar
  10. 10.
    Thong YK, Woolfson MS, Crowe JA, Hayes-Gill BR, Jones DA (2004) Numerical double integration of acceleration measurement in noise. Measurement 36: 73–92CrossRefGoogle Scholar
  11. 11.
    Yao J, Taylor RH, Goldberg RP, Kumar R, Bzostek A, Van Vorhis R, Kazanzides P, Gueziec A (2000) A C-arm fluoroscopy-guided progressive cut refinement strategy using a surgical robot. Comput Aided Surg 5(6): 373–390CrossRefPubMedGoogle Scholar
  12. 12.
    Zhang NF (2006) Calculation of the uncertainty of the mean of autocorrelated measurements. Metrologia 43: S276–S281CrossRefGoogle Scholar

Copyright information

© CARS 2010

Authors and Affiliations

  1. 1.Laboratory for Percutaneous Surgery, School of ComputingQueen’s UniversityKingstonCanada

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