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

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 (g) 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 g are removed from the PH procedure. The accuracy of the proposed tracking method was found by a simulation study to be approximately 20 mm. We also found, through a phantom experiment, that the value of g sensitively increased enough to detect out-of-plane motion. Most important, g 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.

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

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

“…Computer vision techniques for motion extraction are widely developed in a huge variety of applications, including motion tracking, motion compensation, image registration [ 1 ], remote sensing [ 2 ], biomedicine [ 3 ], satellite imagery [ 4 ] and vibration analysis [ 5 ]. Within this scope, techniques of digital image correlation (DIC) are known to provide accurate results with a high computational efficiency, along with good robustness against noises.…”