Abstract
Ultrasound provides a useful and readily available imaging tool. The big challenge in acquiring a good ultrasound image are possible shadow artefacts that hide anatomical structures. This applies in particular to 3D ultrasound acquisitions, because shadow artefacts may be recorded outside the visualized image plane. There are only a few automatic methods for shadow artefact detection. In our work we like to introduce a new shadow detection method that is based on an adaptive thresholding approach. The development was attempted, after existing methods had been extended to separate shadow and fluid regions. The entire detection procedure utilizes only the ultrasound scan line information and some basic knowledge about the ultrasound propagation inside the human body. Applying our method, the ultrasound operator can retrieve combined information about shadow and fluid locations, that may be invaluable for image acquisition or diagnosis. The method can be applied to conventional 2D as well as 3D ultrasound images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Chan, T., Osher, S., Shen, J.: The digital tv filter and nonlinear denoising. IEEE Trans. Image Process. 10(2), 231–241 (2001)
Hellier, P., Coupe, P., Meyer, P., Morandi, X., Collins, D.: Acoustic shadows detection, application to accurate reconstruction of 3d intraoperative ultrasound. In: 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008, ISBI 2008, pp. 1569–1572, May 2008
Ito, K., Sugano, S., Iwata, H.: Internal bleeding detection algorithm based on determination of organ boundary by low-brightness set analysis. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4131–4136, October 2012
Karamalis, A., Wein, W., Klein, T., Navab, N.: Ultrasound confidence maps using random walks. Med. Image Anal. 16(6), 1101–1112 (2012). http://www.sciencedirect.com/science/article/pii/S1361841512000977
Michailovich, O.V., Tannenbaum, A.: Despeckling of medical ultrasound images. IEEE Trans. Ultrason. Ferroelectr. Freq. Control 53(1), 64–78 (2006). http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3639001/
Noll, M., Puhl, J., Wesarg, S.: Enhanced shadow detection for 3D ultrasound. In: Deserno, T.M., Handels, H., Meinzer, H.-P., Tolxdorff, T. (eds.) Bildverarbeitung für die Medizin 2014. I, pp. 234–239. Springer, Heidelberg (2014). doi:10.1007/978-3-642-54111-7_45
Penney, G., Blackall, J., Hamady, M., Sabharwal, T., Adam, A., Hawkes, D.: Registration of freehand 3d ultrasound and magnetic resonance liver images. Med. Image Anal. 8(1), 81–91 (2004). http://view.ncbi.nlm.nih.gov/pubmed/14644148
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2017 Springer International Publishing AG
About this paper
Cite this paper
Noll, M., Puhl, J., Wesarg, S. (2017). Achieving Fluid Detection by Exploiting Shadow Detection Methods. 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_15
Download citation
DOI: https://doi.org/10.1007/978-3-319-67552-7_15
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-67551-0
Online ISBN: 978-3-319-67552-7
eBook Packages: Computer ScienceComputer Science (R0)