Ultrasound motion estimation using a hierarchical feature weighting algorithm

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

The quality of ultrasonic images is usually influenced by speckle noises and the temporal decorrelation of the speckle patterns. Most traditional motion estimation algorithms are not suitable for speckle tracking in medical ultrasonic images which usually have a low signal-to-noise ratio (SNR). This paper proposes a new motion estimation algorithm that is designed for assessing the dense velocity fields of soft tissue motion in a sequence of ultrasonic B-mode images. We design a hierarchical maximum a posteriori estimator together with an adaptive feature weighted mechanism to estimate the motion field from an ultrasonic image sequence. The proposed method was compared with several existing motion estimation methods via a series of experiments with synthetic speckle image sequences. Performance was also tested on in vivo ultrasonic images. The experimental results show that motion can be assessed with better accuracy than other methods for synthetic speckle images and a good correspondence with clinicians' observations has also been achieved for clinical ultrasonic images.

Original languageEnglish
Pages (from-to)178-190
Number of pages13
JournalComputerized Medical Imaging and Graphics
Volume31
Issue number3
DOIs
Publication statusPublished - 2007 Apr 1

Fingerprint

Motion estimation
Ultrasonics
Speckle
Signal-To-Noise Ratio
Acoustic noise
Signal to noise ratio
Tissue
Experiments

All Science Journal Classification (ASJC) codes

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

Cite this

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abstract = "The quality of ultrasonic images is usually influenced by speckle noises and the temporal decorrelation of the speckle patterns. Most traditional motion estimation algorithms are not suitable for speckle tracking in medical ultrasonic images which usually have a low signal-to-noise ratio (SNR). This paper proposes a new motion estimation algorithm that is designed for assessing the dense velocity fields of soft tissue motion in a sequence of ultrasonic B-mode images. We design a hierarchical maximum a posteriori estimator together with an adaptive feature weighted mechanism to estimate the motion field from an ultrasonic image sequence. The proposed method was compared with several existing motion estimation methods via a series of experiments with synthetic speckle image sequences. Performance was also tested on in vivo ultrasonic images. The experimental results show that motion can be assessed with better accuracy than other methods for synthetic speckle images and a good correspondence with clinicians' observations has also been achieved for clinical ultrasonic images.",
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Ultrasound motion estimation using a hierarchical feature weighting algorithm. / Lin, Cheng Hsien; Lin, Mark Chii Jeng; Sun, Yung Nien.

In: Computerized Medical Imaging and Graphics, Vol. 31, No. 3, 01.04.2007, p. 178-190.

Research output: Contribution to journalArticle

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