Abstract
Ultrasound (US) B-mode images often show intensity inhomogeneities caused by an ultrasonic beam attenuation within the body. Due to this artifact, the conventional segmentation approaches based on intensity or intensity-statistics often do not obtain accurate results. In this paper, Markov Random Fields (MRF) and a maximum a posteriori (MAP) framework in combination with US image spatial information is used to estimate the distortion field in order to correct the image while segmenting regions of similar intensity inhomogeneity. The proposed approach has been evaluated using a set of 56 breast B-mode US images and compared to a radiologist segmentation.
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© 2011 Springer-Verlag Berlin Heidelberg
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Pons, G., Martí, J., Martí, R., Noble, J.A. (2011). Simultaneous Lesion Segmentation and Bias Correction in Breast Ultrasound Images. In: Vitrià, J., Sanches, J.M., Hernández, M. (eds) Pattern Recognition and Image Analysis. IbPRIA 2011. Lecture Notes in Computer Science, vol 6669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21257-4_86
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DOI: https://doi.org/10.1007/978-3-642-21257-4_86
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-21256-7
Online ISBN: 978-3-642-21257-4
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