Simultaneous lesion segmentation and bias correction in breast ultrasound images

Authors:
Gerard Pons;Joan Martí;Robert Martí;J. Alison Noble
Affiliations:
Department of Computer Architecture and Technology, University of Girona, Girona, Spain;Department of Computer Architecture and Technology, University of Girona, Girona, Spain;Department of Computer Architecture and Technology, University of Girona, Girona, Spain;Department of Engineering Science, University of Oxford, Oxford, United Kingdom
Venue:
IbPRIA'11 Proceedings of the 5th Iberian conference on Pattern recognition and image analysis
Year:
2011

Citing 3
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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.