3-D Bayesian ultrasound breast image segmentation using the EM/MPM algorithm

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Author

LA Christopher, EJ Delp, CR Meyer, PL Carson

Entry type

article

Abstract

In this paper, ultrasound breast image segmentation is improved by using the volumetric data available in neighboring slices. The new algorithm extends the EM/MPM framework to 3D by including pixels from neighboring frames in the Markov Random Field (MRF) clique. In addition, this paper describes a unique linear cost factor introduced in the optimization loop to compensate for the attenuation common to ultrasound images.

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Date

2002

Journal

Biomedical Imaging, 2002. Proceedings. 2002 IEEE International Symposium on

Key alpha

Delp

Pages

86-89

Publication Date

2002-01-01

Keywords

Bayes methods, Markov processes, biomedical ultrasonics, image segmentation, mammography, medical image processing, optimisation, ultrasonic absorption 3-D Bayesian ultrasound breast image segmentation, EM/MPM algorithm, Markov Random Field clique, attenuation compensation, medical diagnostic imaging, neighboring frames, optimization loop, pixels, ultrasound images, unique linear cost factor

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@Article{ Delp,
	title = "3-D Bayesian ultrasound breast image segmentation using the EM/MPM algorithm",
	author = "LA Christopher, EJ Delp, CR Meyer, PL Carson",
	year = "2002",
	journal = "Biomedical Imaging, 2002. Proceedings. 2002 IEEE International Symposium on",
	pages = "86-89",
	abstract = "In this paper, ultrasound breast image segmentation is improved by using the volumetric data available in neighboring slices. The new algorithm extends the EM/MPM framework to 3D by including pixels from neighboring frames in the Markov Random Field (MRF) clique. In addition, this paper describes a unique linear cost factor introduced in the optimization loop to compensate for the attenuation common to ultrasound images.",
	keywords = "Bayes methods, Markov processes, biomedical ultrasonics, image segmentation, mammography, medical image processing, optimisation, ultrasonic absorption 3-D Bayesian ultrasound breast image segmentation, EM/MPM algorithm, Markov Random Field clique, attenuation compensation, medical diagnostic imaging, neighboring frames, optimization loop, pixels, ultrasound images, unique linear cost factor",
}