3-D Bayesian ultrasound breast image segmentation using the EM/MPM algorithm
Tóm tắt
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.
Từ khóa
#Bayesian methods #Ultrasonic imaging #Breast #Image segmentation #Markov random fields #Magnetic resonance imaging #Acoustic noise #Image processing #Cost function #AttenuationTài liệu tham khảo
10.1016/S0929-8266(98)00062-7
10.1109/83.869185
10.2307/2289127
10.1109/58.895909
10.1109/42.650884
10.1109/42.650883
moon, 1999, The Expectation-Maximization algorithm, IEEE Signal Processing Magazine, 47
10.1016/0301-5629(95)00018-M
10.1016/S1361-8415(97)85010-4
10.1109/TPAMI.1984.4767596
besag, 1974, Spatial interaction and the statistical analysis of lattice systems, J R Stat Soc B, 36, 192
10.1109/83.913586
10.1109/83.941855
10.1016/S0301-5629(00)00286-6
10.1109/58.981389
10.1109/10.951522