Paper
17 March 2015 Research on respiratory motion correction method based on liver contrast-enhanced ultrasound images of single mode
Ji Zhang, Tao Li, Shiqiang Zheng, Yiyong Li
Author Affiliations +
Abstract
To reduce the effects of respiratory motion in the quantitative analysis based on liver contrast-enhanced ultrasound (CEUS) image sequencesof single mode. The image gating method and the iterative registration method using model image were adopted to register liver contrast-enhanced ultrasound image sequences of single mode. The feasibility of the proposed respiratory motion correction method was explored preliminarily using 10 hepatocellular carcinomas CEUS cases. The positions of the lesions in the time series of 2D ultrasound images after correction were visually evaluated. Before and after correction, the quality of the weighted sum of transit time (WSTT) parametric images were also compared, in terms of the accuracy and spatial resolution. For the corrected and uncorrected sequences, their mean deviation values (mDVs) of time-intensity curve (TIC) fitting derived from CEUS sequences were measured. After the correction, the positions of the lesions in the time series of 2D ultrasound images were almost invariant. In contrast, the lesions in the uncorrected images all shifted noticeably. The quality of the WSTT parametric maps derived from liver CEUS image sequences were improved more greatly. Moreover, the mDVs of TIC fitting derived from CEUS sequences after the correction decreased by an average of 48.48±42.15. The proposed correction method could improve the accuracy of quantitative analysis based on liver CEUS image sequences of single mode, which would help in enhancing the differential diagnosis efficiency of liver tumors.
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Ji Zhang, Tao Li, Shiqiang Zheng, and Yiyong Li "Research on respiratory motion correction method based on liver contrast-enhanced ultrasound images of single mode", Proc. SPIE 9419, Medical Imaging 2015: Ultrasonic Imaging and Tomography, 941912 (17 March 2015); https://doi.org/10.1117/12.2081134
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KEYWORDS
Liver

Image registration

Ultrasonography

Quantitative analysis

Tumors

Toxic industrial chemicals

Image enhancement

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