Abstract
Computer assisted fluoroscopic navigation has received strong interest as a new tool for various medical interventions (e.g. spinal, orthopaedic and brachytherapy procedures). One of the challenges for the intraoperative use of c-arm imaging is on-line calibration [1,2]. Usually the method selected to perform this task involves placing a grid of fiducial markers in the x-ray path. The real geometry of the grid is known, so if the geometry of the grid in the image can be found then the real location of the other features in the image can be determined. Detection of the markers is the most important step in the calibration process [2]. This paper describes a new technique for automatic detection of markers. The purpose is to detect the highest number of markers as possible from a standard grid. As a convenience, removal of the detected markers is also proposed.
Software: http://www.ece.ubc.ca/~neculaia/Matlab_code_fluoroscopy.htm
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Tate, P., Lachine, V., Fu, L., Croitoru, H., Sati, M.: Performance and Robustness of Automatic Fluoroscopic Image Calibration in a New Computer Assisted Surgery System. In: Niessen, W.J., Viergever, M.A. (eds.) MICCAI 2001. LNCS, vol. 2208, pp. 1130–1136. Springer, Heidelberg (2001)
Livyatan, H., Yaniv, Z., Joskowicz, L.: Robust automatic C-arm calibration for fluoroscopy-based navigation: a practical approach. In: Dohi, T., Kikinis, R. (eds.) MICCAI 2002. LNCS, vol. 2489, pp. 60–68. Springer, Heidelberg (2002)
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Smith, L., Pleasance, M., Seeton, R., Archip, N., Rohling, R. (2004). Automatic Detection and Removal of Fiducial Markers Embedded in Fluoroscopy Images for Online Calibration. In: Barillot, C., Haynor, D.R., Hellier, P. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2004. MICCAI 2004. Lecture Notes in Computer Science, vol 3217. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30136-3_125
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DOI: https://doi.org/10.1007/978-3-540-30136-3_125
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