论文信息 - Maximum likelihood motion estimation in ultrasound image sequences

Maximum likelihood motion estimation in ultrasound image sequences

Maximum likelihood (ML) techniques are defined for optimum block matching to enable motion estimation sequences of ultrasound B-mode images. Such motion estimation is needed as a diagnostic tool in medical use of ultrasound imagery. It is also needed for the efficient compression of sequences of ultrasound images. The novel ML block matching techniques correspond to accurate statistical descriptions of ultrasound images, and are evaluated experimentally using sequences of transesophageal ultrasound images of the heart.

M. Strintzis | I. Kokkinidis

[1] Athanasios Papoulis,et al. Probability, Random Variables and Stochastic Processes , 1965 .

[2] Bruno O. Shubert,et al. Random variables and stochastic processes , 1979 .

[3] Peter H. Westerink,et al. Scalar quantization error analysis for image subband coding using QMFs , 1992, IEEE Trans. Signal Process..

[4] N. Maglaveras,et al. Tumor detection in ultrasound B-mode images through motion estimation using a texture detection algorithm , 1994, Computers in Cardiology 1994.

[5] Michael G. Strintzis,et al. Nonlinear ultrasonic image processing based on signal-adaptive filters and self-organizing neural networks , 1994, IEEE Trans. Image Process..

[6] M. G. Strintzis,et al. Bayesian contour estimation of the left ventricle in ultrasound images of the heart , 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.

[7] Michael G. Strintzis,et al. Lossless coding and visualization of 3‐D medical images with lossy preview capability , 1996 .

[8] E. Parzen. 1. Random Variables and Stochastic Processes , 1999 .