Automatic Image-based Gating for 4D Ultrasound

Abstract

Four-dimensional (4D) ultrasound can be a powerful tool in adult and fetal echocardiography, enabling physicians to visualize planes that are not easily accessible using 2D ultrasound. However, despite the advances in the transducer technology, gating is still required to avoid motion artifacts during acquisition using mechanical probes or even 2D matrix array transducers in case of extended volume or color Doppler acquisitions. In fetal echocardiography, where an ECG signal is not readily available, image gating is used, which can both be computationally expensive and/or require user interaction. We present a new image gating technique that has both low computational requirements and is fully automatic. It is not only suitable for real-time gating of 4D ultrasound data sets during acquisition, but also suits well for lower-cost systems where computing resources are at a premium.

4D ultrasonic measurements—A new approach using mechanical image dissection techniques

“…The hand sensor may also be used for medical purposes, where lower cost equipment will be an important requirement in future, regarding distributed diagnosis and home healthcare [17].…”

Manifold Learning for Image-Based Breathing Gating with Application to 4D Ultrasound

“…There are several papers on image-based gating in ultrasound for detecting the cardiac motion [1][2][3][4]. These approaches apply techniques that are either (i) specific to detecting the cardiac signal e.g.…”

“…These approaches apply techniques that are either (i) specific to detecting the cardiac signal e.g. centroid algorithm [4], (ii) based on user interaction [1], or (iii) designed for intravascular ultrasound [2,3]. We are only aware of the work of Sundar et al .…”

Image-Based Methods for Phase Estimation, Gating, and Temporal Superresolution of Cardiac Ultrasound

“…Previous work on the estimation of cardiac and/or respiratory phases directly from ultrasound echocardiography videos is limited. In [14], Karadayi et al . compute a signal of the x- or y-coordinate of the center-of-mass of each frame, use a band-pass filter to remove frequencies outside the cardiac range, determine the dominant frequency in the periodogram, and apply matched filtering using single-period sine and cosine signals at the dominant frequency to estimate the instantaneous cardiac phase.…”