Abstract
This paper proposes a probe-camera system for 3D ultrasound (US) image reconstruction with probe-camera calibration and probe localization methods. The probe-camera calibration method employs an existing US phantom for convenience with a simple procedure. The probe localization method employs structure from motion (SfM) to estimate the camera motion. SfM is used to reconstruct 3D point clouds from multiple-view images and simultaneously estimate each camera position. Through experiments using the developed system, we demonstrate that the proposed method exhibits good performance to reconstruct 3D US volume.
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Notes
- 1.
Camera Calibration Toolbox for Matlab: http://www.vision.caltech.edu/bouguetj/calib_doc/.
- 2.
Stradwin: http://mi.eng.cam.ac.uk/~rwp/stradwin.
References
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Comm. ACM 24(6), 381–395 (1981)
Gee, A., Prager, R., Treece, G., Berman, L.: Engineering a freehand 3D ultrasound system. Pattern Recogn. Lett. 24(4–5), 757–777 (2003)
Goldsmith, A., Pedersen, P., Szabo, T.: An inertial-optical tracking system for portable, quantitative, 3D ultrasound. In: IEEE International Ultrasonics Symposium Proceedings, pp. 45–49 (2008)
Hartley, R., Zisserman, A.: Multiple View Geometry. Cambridge University Press, Cambridge (2004)
Hastenteufel, M., Vetter, M., Meinzer, H.P., Wolf, I.: Effect of 3D ultrasound probes on the accuracy of electromagnetic tracking systems. Ultrasound Med. Biol. 32(9), 1359–1368 (2006)
Horvath, S., et al.: Towards an ultrasound probe with vision: structured light to determine surface orientation. In: Linte, C.A., Moore, J.T., Chen, E.C.S., Holmes, D.R. (eds.) AE-CAI 2011. LNCS, vol. 7264, pp. 58–64. Springer, Heidelberg (2012). doi:10.1007/978-3-642-32630-1_6
Ishii, J., Sakai, S., Ito, K., Aoki, T., Yanagi, T., Ando, T.: 3D reconstruction of urban environments using in-vehicle fisheye camera. In: Proceedings of the IEEE International Conference on Image Processing, pp. 2145–2148, September 2013
Ito, S., Ito, K., Aoki, T., Ohmiya, J., Kondo, S.: Probe localization using structure from motion for 3D ultrasound image reconstruction. In: Proceedings of the International Conference on Medical Imaging, pp. 68–71 (2017)
Kneip, L., Scaramuzza, D., Siegwart, R.: A novel parametrization of the perspective-three-point problem for a direct computation of absolute camera position and orientation. In: Proceedings of the International Conference Computer Vision and Pattern Recognition, pp. 2969–2976 (2011)
Lange, T., Kraft, S., Eulenstein, S., Lamecker, H., Schlag, P.: Automatic calibration of 3D ultrasound probes. In: Handels, H., Ehrhardt, J., Deserno, T., Meinzer, H.P., Tolxdorff, T. (eds.) Bildverarbeitung fur die Medizin 2011, pp. 169–173. Springer, Heidelberg (2011). doi:10.1007/978-3-642-19335-4_36
Nistér, D.: An efficient solution to the five-point relative pose problem. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 756–770 (2004)
Rafii-Tari, H., Abolmaesumi, P., Rohling, R.: Panorama ultrasound for guiding epidural anesthesia: a feasibility study. In: Taylor, R.H., Yang, G.-Z. (eds.) IPCAI 2011. LNCS, vol. 6689, pp. 179–189. Springer, Heidelberg (2011). doi:10.1007/978-3-642-21504-9_17
Rousseau, F., Hellier, P., Barillot, C.: A fully automatic calibration procedure for freehand 3D ultrasound. In: Proceedings of the IEEE International Symposium Biomedical, Imaging, pp. 985–988 (2002)
Shi, J., Tomasi, C.: Good features to track. In: Proceedings of the International Conference on Computer Vision and Pattern Recognition, pp. 593–600 (1994)
Stolka, P., Kang, H., Choti, M., Boctor, E.: Multi-DoF probe trajectory reconstruction with local sensors for 2D-to-3D ultrasound. In: Proceedings of the IEEE International Symposium Biomedical, Imaging, pp. 316–319 (2010)
Sun, S.-Y., Gilbertson, M., Anthony, B.W.: Probe localization for freehand 3D ultrasound by tracking skin features. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds.) MICCAI 2014. LNCS, vol. 8674, pp. 365–372. Springer, Cham (2014). doi:10.1007/978-3-319-10470-6_46
Szeliski, R.: Computer Vision: Algorithms and Applications. Springer-Verlag New York Inc., New York (2010). doi:10.1007/978-3-642-12848-6
Takita, K., Muquit, M.A., Aoki, T., Higuchi, T.: A sub-pixel correspondence search for computer vision applications. IEICE Trans. Fundam. E87–A(8), 1913–1923 (2004)
Zhang, Z.: Iterative point matching for registration of free-form curves and surfaces. Int. J. Comput. Vis. 13(2), 119–152 (1994)
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Ito, K., Yodokawa, K., Aoki, T., Ohmiya, J., Kondo, S. (2017). A Probe-Camera System for 3D Ultrasound Image Reconstruction. In: Cardoso, M., et al. Imaging for Patient-Customized Simulations and Systems for Point-of-Care Ultrasound. BIVPCS POCUS 2017 2017. Lecture Notes in Computer Science(), vol 10549. Springer, Cham. https://doi.org/10.1007/978-3-319-67552-7_16
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