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http://dx.doi.org/10.3745/KTSDE.2020.9.2.69

Parametric Imaging with Respiratory Motion Correction for Contrast-Enhanced Ultrasonography  

Kim, Ho-Joon (한동대학교 전산전자공학부)
Cho, Yun-Seok (한동대학교 전산전자공학부)
Publication Information
KIPS Transactions on Software and Data Engineering / v.9, no.2, 2020 , pp. 69-76 More about this Journal
Abstract
In this paper, we introduce a method to visualize the contrast diffusion patterns and the dynamic vascular patterns in a contrast-enhanced ultrasound image sequence. We present an imaging technique to visualize parameters such as contrast arrival time, peak intensity time, and contrast decay time in contrast-enhanced ultrasound data. The contrast flow pattern and its velocity are important for characterizing focal liver lesions. We propose a method for representing the contrast diffusion patterns as an image. In the methods, respiratory motion may degrade the accuracy of the parametric images. Therefore, we present a respiratory motion tracking technique that uses dynamic weights and a momentum factor with respect to the respiration cycle. Through the experiment using 72 CEUS data sets, we show that the proposed method makes it possible to overcome the limitation of analysis by the naked eye and improves the reliability of the parametric images by compensating for respiratory motion in contrast-enhanced ultrasonography.
Keywords
Image Processing; Ultrasound Image; Parametric Imaging; Motion Tracking; Respiratory Motion;
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