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

Author

Christopher, Lauren A. ; Delp, Edward J. ; Meyer, Charles R. ; Carson, Paul L.

Author_Institution

Video & Image Process. Lab., Purdue Univ., West Lafayette, IN, USA

fYear

2002

fDate

2002

Firstpage

86

Lastpage

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; Acoustic noise; Attenuation; Bayesian methods; Breast; Cost function; Image processing; Image segmentation; Magnetic resonance imaging; Markov random fields; Ultrasonic imaging;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Print_ISBN

0-7803-7584-X

Type

conf

DOI

10.1109/ISBI.2002.1029199

Filename

1029199