Abstract
Ultrasound backscattering signals depend on the microstructures of tissues. Some studies have applied Shannon entropy to analyze the uncertainty of raw radiofrequency (RF) data. However, we found that the sensitivity of entropy in detecting various scatterer concentrations is limited; thus, we propose a weighted entropy as a new information entropy-based approach to enhance the performance of scatterer characterization. A standard simulation model of ultrasound backscattering was used to generate backscattered RF signals with different number densities of scatterers. The RF signals were used to estimate the weighted entropy according to the proposed algorithmic scheme. The weighted entropy increased from 0.08 to 0.23 (representing a dynamic range of 0.15) when the number density of scatterers increased from 2 to 32 scatterers/mm2. In the same range of scatterer concentration, the conventional entropy increased from 0.16 to 0.19 (a dynamic range of 0.03). The results indicated that the weighted entropy enables achieving a more sensitive detection of the variation of scatterer concentrations by ultrasound.
Highlights
Ultrasound B-mode imaging is an important imaging modality because of its cost effectiveness, nonionizing radiation, real-time capability, and widespread applicability in various clinical settings.Ultrasound scattering occurs when the wavelength of an incident ultrasound signal is greater than the sizes of scatterers in a tissue, and the scattering results in a speckle pattern in a B-mode image
The results indicated that the weighted entropy enables achieving a more sensitive detection of the variation of scatterer concentrations by ultrasound
We recently evaluated entropy measures and our preliminary tests in the laboratory showed that the standard Shannon entropy estimation by using raw RF data is not sensitive to the variation in the scatterer concentration
Summary
Ultrasound scattering occurs when the wavelength of an incident ultrasound signal is greater than the sizes of scatterers in a tissue, and the scattering results in a speckle pattern in a B-mode image. Different arrangements of scatterers in a medium result in different tissue microstructures, producing distinct envelope statistics that can be modeled using mathematical statistical distributions to characterize tissues quantitatively [1]. Rayleigh distribution is the first model used to describe the envelope statistics of ultrasound signals [2]. The distribution of the backscattered envelope conforms to the Rayleigh distribution when the resolution cell of the ultrasound transducer contains numerous randomly distributed scatterers. The scatterers in most biological tissues can be arranged in various manners. Estimation methods for the parameters of the K models have been explored [7,8,9,10]
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