Abstract
Ultrasound-Guided Regional Anesthesia is a technique to provide regional anesthesia aided by ultrasound visualization of the region on which the anesthesia will be applied. A proper detection and tracking of the nerve contour is necessary to decide where anesthesia should be applied. If the needle is too far from the nerve contour, the anesthesia could be ineffective, but if it touch the nerve could harm the patient. In this paper we address a model to track nerve contours in ultrasonic videos to assist the doctors during Ultrasound-Guided Regional Anesthesia procedures. The experimental results show that our model performs good within an acceptable margin of error.
Keywords
This work is part of the DANIEAL2 project supported by a Region Centre-Val de Loire (France) grant. We gratefully acknowledge Region Centre-Val de Loire for its support.
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Buades, A., Coll, B., Morel, J.M.: A review of image denoising algorithms, with a new one. Multiscale Model. Simul. 4, 490–530 (2005)
Babenko, B., Yang, M.-H., Belongie, S.J.: Visual tracking with online multiple instance learning. In: Computer Vision and Pattern Recognition, CVPR, pp. 983–990. IEEE (2009)
Canny, J.: A computational approach to edge detection. Pattern Anal. Mach. Intell. 8, 679–698 (1986)
Hadjerci, O., Hafiane, A., Conte, D., Markis, P., Vieyres, P., Delbos., A.: Ultrasound median nerve localization by classification based on despeckle filtering and feature selection. In: 2015 IEEE International Conference on Image Processing, ICIP 2015, Quebec City, QC, Canada, 27–30 September 2015, pp. 4155–4159 (2015)
Hadjerci, O., Hafiane, A., Makris, P., Conte, D., Vieyres, P., Delbos, A.: Nerve detection in ultrasound images using median Gabor binary pattern. In: Campilho, A., Kamel, M. (eds.) ICIAR 2014. LNCS, vol. 8815, pp. 132–140. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-11755-3_15
Hadjerci, O., Hafiane, A., Vieyres, P., Conte, D., Makris, P., Delbos, A.: On-line learning dynamic models for nerve detection in ultrasound videos. In: 2016 IEEE International Conference on Image Processing (ICIP), pp. 131–135. IEEE (2016)
Grabner, H., Grabner, M., Bischof, H.: Real-time tracking via on-line boosting. In: British Machine Vision Conference, BMVC, vol. 1 (2006)
Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: Exploiting the circulant structure of tracking-by-detection with Kernels. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) ECCV 2012. LNCS, vol. 7575, pp. 702–715. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-33765-9_50
Danelljan, M., Khan, F.S., Felsberg, M., van de Weijer, J.: Adaptive color attributes for real-time visual tracking. In: Computer Vision and Pattern Recognition, CVPR, pp. 1090–1097. IEEE (2014)
Marhofer, P., Willschke, H., Kettner, S.: Current concepts and future trends in ultrasound-guided regional anesthesia. Curr. Opin. Anesthesiol. 23(5), 632–636 (2010)
Sezgin, M., Sankur, B.: Survey over image thresholding techniques and quantitative performance evaluation. Electron. Imaging 13, 146–168 (2004)
Thouin, E., Hafiane, A., Vieyres, P., Xylourgos, N., Triantafyllidis, G., Papadourakis, G.: Nerve region segmentation for ultrasound guided local regional anaesthesia (LRA). In: Mediterranean Conference on Information Systems (2011)
Tsui, B.C., Suresh, S.: Ultrasound imaging for regional anesthesia in infants, children, and adolescentsa review of current literature and its application in the practice of extremity and trunk blocks. Anesthesiol. J. Am. Soc. Anesthesiol. 112(2), 473–492 (2010)
Karnati, V., Uliyar, M., Dey, S.: Fast non-local algorithm for image denoising. In: International Conference on Image Processing, ICIP, pp. 3873–3876 (2009)
Woodworth, G.E., Chen, E.M., Horn, J.L.E., Aziz, M.F.: Efficacy of computer-based video and simulation in ultrasound-guided regional anesthesia training. J. Clin. Anesth. 26(3), 212–221 (2014)
Kalal, Z., Mikolajczyk, K., Matas, J.: A computational approach to edge detection. In: International Conference on Pattern Recognition, ICPR, pp. 2756–2759. IEEE (2010)
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Cortés, X., Conte, D., Makris, P. (2019). Nerve Contour Tracking for Ultrasound-Guided Regional Anesthesia. In: Cristani, M., Prati, A., Lanz, O., Messelodi, S., Sebe, N. (eds) New Trends in Image Analysis and Processing – ICIAP 2019. ICIAP 2019. Lecture Notes in Computer Science(), vol 11808. Springer, Cham. https://doi.org/10.1007/978-3-030-30754-7_25
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DOI: https://doi.org/10.1007/978-3-030-30754-7_25
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