Characterization of tissue microstructure using ultrasonic backscatter: Theory and technique for optimization using a Gaussian form factor

2002 ◽  
Vol 112 (3) ◽  
pp. 1202-1211 ◽  
Author(s):  
Michael L. Oelze ◽  
James F. Zachary ◽  
William D. O’Brien
Keyword(s):  
Form Factor ◽  
Tissue Microstructure ◽  
Gaussian Form ◽  
Ultrasonic Backscatter ◽  
Gaussian Form Factor

HADRONIC FORM FACTORS IN THE γp→K+Λ PROCESS

2013 ◽  
Vol 28 (14) ◽  
pp. 1350054 ◽  
Author(s):  
T. MART ◽  
A. K. SARI
Keyword(s):  
Form Factor ◽  
Cross Section ◽  
Form Factors ◽  
Polarization Data ◽  
Gaussian Form ◽  
Isobaric Model ◽  
Double Polarization ◽  
Gaussian Form Factor ◽  
Photo Production ◽  
Dipole Form

We have investigated the effects of different hadronic form factors on the performance of an isobaric model developed for kaon photo-production off the proton. We found that there is no ideal form factor in this case. The dipole and generalized dipole form factors can help to nicely reproduce the differential cross-section and hyperon polarization data. However, in the case of double polarization data Cx and Cz the Gaussian form factor is found to be superior.

Characterization of Tissue Microstructure Scatterer Distribution with Spectral Correlation

1993 ◽  
Vol 15 (3) ◽  
pp. 238-254 ◽  
Author(s):  
Tomy Varghese ◽  
Kevin D. Donohue
Keyword(s):  
Formation Process ◽  
Biological Tissue ◽  
Statistical Parameters ◽  
Spectral Correlation ◽  
Tissue Microstructure ◽  
Power Spectral ◽  
Spectral Peaks ◽  
Ultrasound Signal

Characterization of tissue microstructure from the backscattered ultrasound signal using the spectral autocorrelation (SAC) function provides information about the scatterer distribution in biological tissue. This paper demonstrates SAC capabilities in characterizing periodicities in A-scans due to regularity in the scatterer distribution. The A-scan is modelled as a cyclostationary signal, where the statistical parameters of the signal vary in time with single or multiple periodicities. This periodicity manifests itself as spectral peaks both in the power spectral density (PSD) and in the SAC. Periodicity in the PSD will produce a well defined dominant peak in the cepstrum, which has been used to determine the scatterer spacing. The relationship between the scatterer spacing and the spacing of the spectral peaks is established using a stochastic model of the echo-formation process from biological tissue. The distribution of the scatterers within the microstructure is modelled using a Gamma function, which offers a flexible method of simulating parametric regularity in the scatterer spacing. Simulations of the tissue microstructure for lower orders of regularity indicate that the SAC components reveal information about the scatterer spacing that are not seen in the PSD and the cepstrum. The echo-formation process is tested by simulating microstructure of varying regularity and analyzing their effect on the SAC, PSD and cepstrum. Experimental validation of the simulation results are provided using in vivo scans of the breast and liver tissue that show the presence of significant spectral correlation components in the SAC.

Ultrasonic backscatter characterization of cancellous bone using a general Nakagami statistical model

2019 ◽  
Vol 28 (2) ◽  
pp. 024302 ◽  
Author(s):  
Chengcheng Liu ◽  
Rui Dong ◽  
Boyi Li ◽  
Ying Li ◽  
Feng Xu ◽  
...  
Keyword(s):  
Statistical Model ◽  
Cancellous Bone ◽  
Ultrasonic Backscatter

Characterization of Anomalous Diffusion from MR Signal may be a New Probe to Tissue Microstructure

2006 ◽  
Author(s):  
Evren Ozarslan ◽  
Peter J. Basser ◽  
Timothy M. Shepherd ◽  
Peter E. Thelwall ◽  
Baba C. Vemuri ◽  
...  
Keyword(s):  
Anomalous Diffusion ◽  
Tissue Microstructure

scholarly journals Why Are Viscosity and Nonlinearity Bound to Make an Impact in Clinical Elastographic Diagnosis?

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2379 ◽  
Author(s):  
Guillermo Rus ◽  
Inas H. Faris ◽  
Jorge Torres ◽  
Antonio Callejas ◽  
Juan Melchor
Keyword(s):  
Soft Tissues ◽  
Elastic Parameters ◽  
Tissue Microstructure ◽  
Non Invasive ◽  
Recent Developments ◽  
Mechanical Biomarkers ◽  
Nonlinear Elastic

The adoption of multiscale approaches by the biomechanical community has caused a major improvement in quality in the mechanical characterization of soft tissues. The recent developments in elastography techniques are enabling in vivo and non-invasive quantification of tissues’ mechanical properties. Elastic changes in a tissue are associated with a broad spectrum of pathologies, which stems from the tissue microstructure, histology and biochemistry. This knowledge is combined with research evidence to provide a powerful diagnostic range of highly prevalent pathologies, from birth and labor disorders (prematurity, induction failures, etc.), to solid tumors (e.g., prostate, cervix, breast, melanoma) and liver fibrosis, just to name a few. This review aims to elucidate the potential of viscous and nonlinear elastic parameters as conceivable diagnostic mechanical biomarkers. First, by providing an insight into the classic role of soft tissue microstructure in linear elasticity; secondly, by understanding how viscosity and nonlinearity could enhance the current diagnosis in elastography; and finally, by compounding preliminary investigations of those elastography parameters within different technologies. In conclusion, evidence of the diagnostic capability of elastic parameters beyond linear stiffness is gaining momentum as a result of the technological and imaging developments in the field of biomechanics.

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