A comparison of colour flow imaging algorithms

Since the introduction of medical ultrasound in the 1950s, modern diagnostic ultrasound has progressed to see many major diagnostic tools come into widespread clinical use, such as B-mode imaging, color-flow imaging, and spectral Doppler. New applications, such as panoramic imaging, three-dimensional imaging, and quantitative imaging, are now beginning to be offered on some commercial ultrasound machines and are expected to grow in popularity. In this review, we focus on the various algorithms, their processing requirements, and the challenges of these ultrasound modes. Whereas the older, mature B and color-flow modes could be systolically implemented using hardwired components and boards, new applications, such as three-dimensional imaging and image feature extraction, are being implemented more by using programmable processors. This trend toward programmable ultrasound machines will continue, because the programmable approach offers the advantages of quick implementation of new applications without any additional hardware and the flexibility to adapt to the changing requirements of these dynamic new applications.

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“…Instead, spatial tracking along a scan line (i.e. across a vessel's velocity profile) has been shown to perform well for laminar flow (91).…”

Section: Color-flow Trade-offs and Challengesmentioning

confidence: 99%

Ultrasound Processing and Computing: Review and Future Directions

York

Kim

1999

Annu. Rev. Biomed. Eng.

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“…Techniques for blood flow measurement include pulsed Doppler, power Doppler and color flow imaging (i.e., color Doppler), mainly based on estimation of frequency shift or phase shift due to the Doppler effect (Hoskins 1999). In color flow imaging, in addition to the conventional and widely-used frequency domain auto-correlation (Kasai et al 1985), time domain cross-correlation and other methods have also been developed as alternative approaches, offering aliasing free velocity detection and angle-independent capability (Bonnefous and Pesque 1986, Shariati et al 1993, Trahey et al 1987). …”

Section: Introductionmentioning

confidence: 99%

Imaging of Wall Motion Coupled With Blood Flow Velocity in the Heart and Vessels in Vivo: A Feasibility Study

Luo

Konofagou

2011

Ultrasound in Medicine & Biology

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The mechanical property and geometry changes as a result of disease affect both the wall motion and blood flow, while the latter two are also coupled and therefore continuously influence one another. Simultaneous and registered imaging of both cardiovascular wall motion and blood velocity may thus contribute to more complete computational models of cardiovascular mechanical and fluid dynamics as well as provide additional diagnostic information. The objective of this paper is to determine the feasibility of imaging cardiovascular wall motion coupled with blood flow in vivo. Normal (n=6) and infarcted (n=5) murine left ventricles, and normal (n=5) and aneurysmal (n=4) murine abdominal aortas, were imaged in longitudinal views with a 30-MHz ultrasound probe. Using electrocardiogram (ECG) gating, two-dimensional (2-D) radio-frequency (RF) data were acquired at a frame rate of 8 kHz. The axial wall velocity and blood velocity were estimated using a speckle tracking technique. Spatially and temporally registered imaging of both cardiovascular wall motion and blood flow was shown feasible. Reduced wall motion was detected in the infarcted region, while vortex flow patterns were imaged in diastolic phases of both normal and infarcted left ventricles. The myocardial wall motion and blood flow were found be to more synchronized in the normal heart, where the blood moves towards the anteroseptal wall after the mitral valve opens (i.e., rapid filling phase), and the anteroseptal wall simultaneously undergoes outward motion. In the infarcted heart, however, in the rapid filling phase the basal anteroseptal wall starts moving, about 20 ms before the mitral valve opens and the blood enters the left ventricle. In the normal aorta, the wall motion and blood velocity were uniform and synchronized. In the aneurysmal aorta, reduced and spatially varied wall motion and vortex flow patterns in the aneurysmal sac were found. The wall motion and blood velocity were thus less synchronized in the aneurysmal aorta. Cardiovascular wall motion and blood flow were both imaged in mice in vivo. This dual information may provide important information for the diagnosis of cardiovascular disease as well as essential parameters for biomechanical modeling.

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“…The second technique, called time domain correlation, was developed to overcome the problem of aliasing that is present in autocorrelation. [6][7][8] When flow determination is made by time domain correlation, a series of pulsed ultrasound waves interrogates reflectors along the scan line, and reflector velocity is assessed by the measured time shift in the echo pattern generated by a group of scatterers, such as red blood cells. In this article the time domain method will be discussed by illustrating the processing steps.…”

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confidence: 99%

Tinze Domain Correlation in Color Flow Imaging

Hedrick¹,

Hykes

1994

Journal of Diagnostic Medical Sonography

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Time domain correlation is a relatively new technique used to estimate velocity in color flow imaging. Direct measurement of reflector velocity is obtained by determining the time shift in the echo pattern associated with that reflector using pulsed wave ultrasound. The processing steps in time domain correlation, including gating, fixed echo cancellation, and echo pattern matching, are discussed.imaging, time shift, fixed echo canceller, aliasing, broad bandwidth.Color flow imaging is a relatively new scanning mode that combines gray-scale imaging with twodimensional mapping of How information in real time. Motion is depicted throughout the field of view by superimposing different colors on the two-dimensional, gray-scale image. A single representative velocity at each sampling site is color encoded by hue or intensity of color. By displaying the two-dimensional spatial distribution of the velocities and the temporal changes in these velocity patterns, real-time color how imaging allows flow to be evaluated simultaneously throughout the field of view and enables regions of flow disturbance to be more easily visualized.Two different signal processing techniques are used in commercial color How imaging systems to obtain velocity information. The most common approach is a frequency domain method called autocorrelation.1-5 Autocorrelation detection estimates the mean frequency of the Doppler spectra by manipulating the in-phase and quadrature signals. The second technique, called time domain correlation, was developed to overcome the problem of aliasing that is present in autocorrelation. [6][7][8] When flow determination is made by time domain correlation, a series of pulsed ultrasound waves interrogates reflectors along the scan line, and reflector velocity is assessed by the measured time shift in the echo pattern generated by a group of scatterers, such as red blood cells. In this article the time domain method will be discussed by illustrating the processing steps.

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A comparison of colour flow imaging algorithms

Cited by 10 publications

References 17 publications

Ultrasound Processing and Computing: Review and Future Directions

Ultrasound Processing and Computing: Review and Future Directions

Imaging of Wall Motion Coupled With Blood Flow Velocity in the Heart and Vessels in Vivo: A Feasibility Study

Tinze Domain Correlation in Color Flow Imaging

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