Abstract
Detection of speckle in ultrasound (US) images has been regarded as an important research topic in US imaging, mainly focusing on two specific applications: improving signal to noise ratio by removing speckle noise and, secondly, for detecting speckle patches in order to perform a 3D reconstruction based on speckle decorrelation measures.
A novel speckle detection proposal is presented here showing that detection can be improved based on finding optimally discriminant low order speckle statistics. We describe a fully automatic method for speckle detection and propose and validate a framework to be efficiently applied to real B-scan data, not being published to date. Quantitative and qualitative results are provided, both for real and simulated data.
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Martí, R., Martí, J., Freixenet, J., Vilanova, J.C., Barceló, J. (2007). Optimally Discriminant Moments for Speckle Detection in Real B-Scan Images. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72849-8_31
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DOI: https://doi.org/10.1007/978-3-540-72849-8_31
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72848-1
Online ISBN: 978-3-540-72849-8
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