Abstract
A novel approach to the problem of locating and recognizing anatomical structures of interest in ultrasound (US) video is proposed. While addressing this challenge may be beneficial to US examinations in general, it is particularly useful in situations where portable US probes are used by less experienced personnel. The proposed solution is based on the hypothesis that, rather than their appearance in a single image, anatomical structures are most distinctively characterized by the variation of their appearance as the transducer moves. By drawing on recent advances in the non-linear modeling of video appearance and motion, using an extension of dynamic textures, successful location and recognition is demonstrated on two phantoms. We further analyze computational demands and preliminarily explore insensitivity to anatomic variations.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Block, B.: The Practice of Ultrasound: A Step-by-Step Guide to Abdominal Scanning, 1st edn. Thieme (2004)
Chan, A., Vasconcelos, N.: Classifying video with kernel dynamic textures. In: CVPR, pp. 1–6 (2007)
Chaudry, R., Ravichandran, A., Hager, G., Vidal, R.: Histograms of oriented optical flow and binet-cauchy kernels on nonlinear dynamical systems for recognition of human actions. In: CVPR, pp. 1932–1939 (2009)
De Cock, K., Moore, B.: Subspace angles between linear stochastic models. In: CDC, pp. 1561–1566 (2000)
Doretto, G., Chiuso, A., Wu, Y., Soatto, S.: Dynamic textures. Int. J. Comput. Vision 51(2), 91–109 (2001)
Martin, R.: A metric for ARMA processes. IEEE Trans. Signal Process. 48(4), 1164–1170 (2000)
Sohail, A., Rahman, M., Bhattacharya, P., Krishnamurthy, S., Mudur, S.: Retrieval and classification of ultrasound images of ovarian cysts combining texture features and histogram moments. In: ISBI, pp. 288–291 (2010)
Spencer, J.: Utility of portable ultrasound in a community in Ghana. J. Ultrasound Med. 27(12), 1735–1743 (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kwitt, R., Vasconcelos, N., Razzaque, S., Aylward, S. (2012). Recognition in Ultrasound Videos: Where Am I?. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33454-2_11
Download citation
DOI: https://doi.org/10.1007/978-3-642-33454-2_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33453-5
Online ISBN: 978-3-642-33454-2
eBook Packages: Computer ScienceComputer Science (R0)