Effect of Adaptive Threshold Filtering on Ultrasonic Nakagami Parameter to Detect Variation in Scatterer Concentration

Abstract

The Nakagami parameter is associated with the Nakagami distribution estimated from ultrasonic backscattered signals and closely reflects the scatterer concentrations in tissues. There is an interest in exploring the possibility of enhancing the ability of the Nakagami parameter to characterize tissues. In this paper, we explore the effect of adaptive thresholdfiltering based on the noise-assisted empirical mode decomposition of the ultrasonic backscattered signals on the Nakagami parameter as a function of scatterer concentration for improving the Nakagami parameter performance. We carried out phantom experiments using 5 MHz focused and nonfocused transducers. Before filtering, the dynamic ranges of the Nakagami parameter, estimated using focused and nonfocused transducers between the scatterer concentrations of 2 and 32 scatterers/mm3, were 0.44 and 0.1, respectively. After filtering, the dynamic ranges of the Nakagami parameter, using the focused and nonfocused transducers, were 0.71 and 0.79, respectively. The experimental results showed that the adaptive threshold filter makes the Nakagami parameter measured by a focused transducer more sensitive to the variation in the scatterer concentration. The proposed method also endows the Nakagami parameter measured by a nonfocused transducer with the ability to differentiate various scatterer concentrations. However, the Nakagami parameters estimated by focused and nonfocused transducers after adaptive threshold filtering have different physical meanings: the former represents the statistics of signals backscattered from unresolvable scatterers while the latter is associated with stronger resolvable scatterers or local inhomogeneity due to scatterer aggregation.

Acoustic structure quantification by using ultrasound Nakagami imaging for assessing liver fibrosis

“…The detailed techniques of Nakagami parameter estimation and imaging were described previously142829. In brief, (i) The envelope image was obtained using the absolute value of the Hilbert Transform of each echo signal filtered using empirical mode decomposition28; (ii) A square window within the envelope image was used to collect local amplitude data for estimating the Nakagami parameter, which is assigned as the new pixel located in the center of the window.…”

“…In brief, (i) The envelope image was obtained using the absolute value of the Hilbert Transform of each echo signal filtered using empirical mode decomposition28; (ii) A square window within the envelope image was used to collect local amplitude data for estimating the Nakagami parameter, which is assigned as the new pixel located in the center of the window. The side length of the window was three times the pulse length of the transducer1424252729.…”

Empirical Mode Decomposition of Ultrasound Imagingfor Gain-Independent Measurement on Tissue Echogenicity: A Feasibility Study

“…EMD has been widely applied in resolving several engineering and scientific problems [18]. Increasingly, more studies have investigated EMD applications in the field of medical ultrasound imaging, including tissue harmonic imaging [17], signal filtering [19], improvements in tissue characterization by using statistical parameters [20,21], image contrast enhancement [22,23], and elastography construction [24].This study is the first to explain how EMD eliminates the effects of the system gain from echogenicity measurement.…”

Automatic Cataract Hardness Classification Ex Vivo by Ultrasound Techniques

“…The Nakagami parametric image is a 2-D representation of the m values, where a sliding window with width three times the transducer pulse length (0.39 ms) was selected in order to provide good resolution (Tsui et al 2006), which corresponds to 78 samples for the used sampling frequency (200 MHz) and 99% overlapping. To reduce the noise, an adaptive threshold filter was applied to the backscattered signals before the Nakagami parametric image construction (Tsui et al 2010a). …”