Literature DB >> 31837889

Ultrasound Sub-pixel Motion-tracking Method with Out-of-plane Motion Detection for Precise Vascular Imaging.

Hideki Yoshikawa1, Taku Yamamoto2, Tomohiko Tanaka2, Ken-Ichi Kawabata2, Shin Yoshizawa3, Shin-Ichiro Umemura3.   

Abstract

Ultrasound vascularity imaging provides important information for differential diagnosis of tumors. Peak-hold (PH) is a useful technique for precisely imaging small vessels by selecting a maximum brightness in each pixel through the frames obtained sequentially. To use PH successfully one needs motion compensation to reduce image blur, but out-of-plane motion cannot be avoided. To address this problem, we developed a sub-pixel motion-tracking method with out-of-plane motion detection (OPMD). It is a combination of the sum of the absolute differences (SAD) method and the Kanade-Lucas-Tomasi method and can be accurately applied to various motions. The value from OPMD (γ) is defined as a statistical value obtained from the distribution of residual values in the SAD procedure with the obtained frames. The value is ideally 0, and the frames having large γ are removed from the PH procedure. The accuracy of the proposed tracking method was found by a simulation study to be approximately 20 μm. We also found, through a phantom experiment, that the value of γ sensitively increased enough to detect out-of-plane motion. Most important, γ begins to increase before tracking errors occur. This suggests that OPMD can be used to predict tracking errors and effectively remove frames from the PH procedure. An in vivo experiment with a rabbit showed that the PH image obtained with motion tracking clearly revealed peripheral vessels that were blurred in the PH image obtained without motion tracking. We also found that the image quality becomes better when OPMD was used to remove frames including out-of-plane motion.
Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Contrast agent; Motion tracking; Out-of-plane motion; Peak-hold; Sub-pixel; Vascular imaging

Year:  2019        PMID: 31837889     DOI: 10.1016/j.ultrasmedbio.2019.11.005

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  3 in total

1.  Displacement detection with sub-pixel accuracy and high spatial resolution using deep learning.

Authors:  Mariko Yamamoto; Shin Yoshizawa
Journal:  J Med Ultrason (2001)       Date:  2021-11-27       Impact factor: 1.314

2.  Application of Digital Image Based on Machine Learning in Media Art Design.

Authors:  Ciguli Wu
Journal:  Comput Intell Neurosci       Date:  2021-11-22

3.  On Quadratic Interpolation of Image Cross-Correlation for Subpixel Motion Extraction.

Authors:  Bian Xiong; Qinghua Zhang; Vincent Baltazart
Journal:  Sensors (Basel)       Date:  2022-02-08       Impact factor: 3.576

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.