Use of Nakagami Statistics and Empirical Mode Decomposition for Ultrasound Tissue Characterization by a Nonfocused Transducer

Tsui, Po-Hsiang; Chang, Chien‐Cheng; Ho, Ming‐Chih; Lee, Yu-Hsin; Chen, Yung‐Sheng; Chang, Chien-Chung; Huang, Norden E.; Wu, Zhaohua; Chang, King‐Jen

doi:10.1016/j.ultrasmedbio.2009.08.003

Cited by 29 publications

(19 citation statements)

References 45 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…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.…”

Section: Discussionmentioning

confidence: 99%

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

Zhou

et al. 2017

Applied Sciences

Self Cite

View full text Add to dashboard Cite

Empirical mode decomposition (EMD) is an adaptive method for decomposing a signal into intrinsic mode functions (IMFs).This study explored using EMD of ultrasound imaging for gain-independent measurements on tissue echogenicity. The IMF-based echogenicity ratio (IER) was proposed using the first (C 1 ) and second IMFs (C 2 ) of ultrasound radiofrequency data. Experiments on lipid phantoms were conducted to investigate the practical performance of IER. Phantoms with lipid concentrations 0%-30% (n = 36) were scanned using a clinical ultrasound scanner to acquire the radiofrequency data under different gains (12-33 dB) for EMD and IER calculations. Experiments on a tissue-mimicking phantom were further performed using the same ultrasound system and data acquisition procedure to investigate the effect of ultrasound frequency on the IER at5-8 MHz.Experimental results showed that the IER measured under 33-dB gain decreased from 6.65 ± 0.23 to 3.97 ± 0.10 when the lipid concentrations were increased from 0% to 30%. When 12-dB gain was used, the IER decreased from 6.21 ± 0.29 to 3.39 ± 0.07. However, whenincreasing the frequency, the IER had a mean decreasing rate of −8.67% per MHz, which was lower than those of the C 1 and C 2 intensities.The proposed IER may allow gain-independent measurement on tissue echogenicity.

show abstract

Section: Discussionmentioning

confidence: 99%

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

Zhou

et al. 2017

Applied Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…The aforementioned assumption implies that the formation of fatty liver is a process involving the increasing number density of fatty vesicles in the liver parenchyma. Increasing the scatterer concentration, not only generates a stronger effect of constructive wave interference to cause the echo amplitude distribution to vary toward the Rayleigh distribution [46], but also leads to a larger backscattered amplitude [47,48]. In this condition, various echo amplitudes exist, and the signal uncertainty and unpredictability (entropy) increase [33].…”

Section: Effects Of Fatty Infiltration On Ultrasound Entropymentioning

confidence: 99%

Effects of Fatty Infiltration of the Liver on the Shannon Entropy of Ultrasound Backscattered Signals

Tsui

Wan

2016

Entropy

Self Cite

View full text Add to dashboard Cite

This study explored the effects of fatty infiltration on the signal uncertainty of ultrasound backscattered echoes from the liver. Standard ultrasound examinations were performed on 107 volunteers. For each participant, raw ultrasound image data of the right lobe of liver were acquired using a clinical scanner equipped with a 3.5-MHz convex transducer. An algorithmic scheme was proposed for ultrasound B-mode and entropy imaging. Fatty liver stage was evaluated using a sonographic scoring system. Entropy values constructed using the ultrasound radiofrequency (RF) and uncompressed envelope signals (denoted by H R and H E , respectively) as a function of fatty liver stage were analyzed using the Pearson correlation coefficient. Data were expressed as the median and interquartile range (IQR). Receiver operating characteristic (ROC) curve analysis with 95% confidence intervals (CIs) was performed to obtain the area under the ROC curve (AUC). The brightness of the entropy image typically increased as the fatty stage varied from mild to severe. The median value of H R monotonically increased from 4.69 (IQR: 4.60-4.79) to 4.90 (IQR: 4.87-4.92) as the severity of fatty liver increased (r = 0.63, p < 0.0001). Concurrently, the median value of H E increased from 4.80 (IQR: 4.69-4.89) to 5.05 (IQR: 5.02-5.07) (r = 0.69, p < 0.0001). In particular, the AUCs obtained using H E (95% CI) were 0. 93 (0.87-0.99), 0.88 (0.82-0.94), and 0.76 (0.65-0.87) for fatty stages ≥mild, ≥moderate, and ≥severe, respectively. The sensitivity, specificity, and accuracy were 93.33%, 83.11%, and 86.00%, respectively (≥mild). Fatty infiltration increases the uncertainty of backscattered signals from livers. Ultrasound entropy imaging has potential for the routine examination of fatty liver disease.

show abstract

“…Ultrasound backscattered signals are typically formed from the acoustic interference between the incident wave and the scatterers in a tissue. When the number density of scatterers is increased, the effect of constructive wave interference causes the distribution of the backscattered statistics to vary toward the Rayleigh distribution [13] and also leads to larger backscattered echoes [33]. Strong scatterers or an aggregation of scatterers also result in the formation of high-amplitude signals [34].…”

Section: Ultrasound Weighted Entropymentioning

confidence: 99%

“…Such a physical link between the weighted entropy and the tissue microstructure is clinically meaningful and applicable. However, it should be noted that the envelope statistics depend on several factors, such as frequency [18], transducer focusing [33], noise interference [40,46], and acoustic attenuation [42]. The properties of the backscattered signals are also affected by the types of scatterers [41], imaging steering [47], and compounding process [47].…”

Section: Figurementioning

confidence: 99%

Ultrasound Detection of Scatterer Concentration by Weighted Entropy

Tsui

2015

Entropy

Self Cite

View full text Add to dashboard Cite

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/mm 2 . 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.

show abstract

Use of Nakagami Statistics and Empirical Mode Decomposition for Ultrasound Tissue Characterization by a Nonfocused Transducer

Cited by 29 publications

References 45 publications

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

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

Effects of Fatty Infiltration of the Liver on the Shannon Entropy of Ultrasound Backscattered Signals

Ultrasound Detection of Scatterer Concentration by Weighted Entropy

Contact Info

Product

Resources

About