Biomedical subjects

M Bilgen

Publications and source records attributed to M Bilgen.

6 recordsLinked to original sources

PubMed1998

Elastostatics of a spherical inclusion in homogeneous biological media.

A three-dimensional spherical inclusion model that approximates a lesion bonded to a tissue matrix is proposed for biomedical elastography. Analytical formulae describing spatial strain and stress distributions generated in infinite media by uniform loading are given under a linear, homogeneous, isotropic elasticity assumption. Strain and stress distributions are also calculated using finite-element analysis (FEA) for a variety of cases to determine the effects of shear modulus distribution, external loading conditions (uniform stress versus uniform displacement), compressor size and matrix dimensions on the elastostatics of the tissue. Analytical strain and stress predictions are shown to agree with the FEA results to within 10% accuracy provided that the matrix dimensions are at least ten times that of the inclusion. Also for these cases, uniform-stress boundary conditions can be equivalently represented by uniform displacement of the boundary. Spherical inclusions exhibit a lower efficiency for transferring elastic shear modulus contrast into strain contrast than cylindrical or planar inclusions. Additional compression will increase the strain contrast. However, large compressions also lead to increases in ultrasonic signal decorrelation and strain and stress concentrations in the homogeneous matrix around the inclusion. Although strain concentrations may help describe the boundaries of the inclusion more clearly, they also increase the risk of damaging the tissue. Understanding the strain and stress distributions in a biological tissue containing a lesion is necessary for optimizing the experimental configurations and consequently improving the diagnostic values of elasticity imaging.

Cysts↗

PubMed1997

The nonstationary strain filter in elastography: Part II. Lateral and elevational decorrelation.

The nonstationary evolution of the strain filter due to lateral and elevational motion of the tissue scatterers across the ultrasound beam is analyzed for the 1-D cross-correlation-based strain estimator. The effective correlation coefficient that includes the contributions due to lateral and elevational signal decorrelation is used to derate the upper bound of the signal-to-noise ratio in the elastogram (SNRe) predicted by the ideal strain filter. In the case of an elastically homogeneous target, if the transducer is on the axis of symmetry of such target in the elevational direction, the motion of the scatterers out the imaging plane is minimized. In addition, the ultrasound beam along the elevational direction is broader, allowing scatterers to stay longer within the beam during tissue compression. Under these conditions, lateral signal decorrelation becomes the primary contributor to the nonstationary behavior of the strain filter. Both the elastographic SNRe and the dynamic range are reduced, with an increase in lateral decorrelation. Finite element simulations and phantom experiments are presented in this paper to corroborate the theoretical strain filter. The nonstationary behavior of the strain filter is reduced by confining the tissue in the lateral direction (minimizing motion of tissue scatterers), thereby improving the quality of the elastogram.

Computer Simulation↗

PubMed1997

Error analysis in acoustic elastography. I. Displacement estimation.

Correlation between acoustic echo signals obtained before and after application of an external compressional force provides information about the internal deformation of an elastic medium. In this paper, the variance for displacement estimated from an echo data segment and the covariance between two windowed segments that may overlap are derived. The signal and noise spectra are Gaussian and independent. The dependence of the displacement variance on input signal-to-noise ratio (SNRi), time-bandwidth product W, fractional bandwidth Y-1, and the rate of displacement variation with depth a is investigated. The relationship between a and the other experimental parameters is crucial for understanding how signal decorrelation affects displacement error. The expression for displacement variance reduces to the Cramer-Rao lower bound result when a = 0 and W > > 1 for both bandpass and base-band signals. When a not equal to 0 displacement variance increases, and there is an optimal window length at W = square root of 20/a square root of 1 + Y2 for which the displacement variance is minimum. Narrow-band signals produce larger errors than broadband signals for long observation windows when a not equal to 0 and just the opposite when a = 0. Errors are greatest for displacements estimated from the envelope of narrow-band signals. Finally, a general expression for the minimum displacement variance for arbitrary signal and noise spectra is derived as a function of the experimental parameters. These results form a framework for analyzing strain estimates in elastography, the subject of a companion paper.

Acoustics↗

PubMed1997

Error analysis in acoustic elastography. II. Strain estimation and SNR analysis.

Accurate displacement estimates are required to obtain high-quality strain estimates in elastography. In this paper the strain variance is derived from the statistical properties of the displacement field to define a point signal-to-noise ratio for elastography (SNR0). Displacements caused by compressional forces applied along the axis of the transducer beam are modeled by scaling and shifting the axial reflectivity profile of the tissue. The strain variance is given as a function of essential experimental parameters, such as the amount of tissue compression, echo waveform window length, and the amount of window overlap. SNR0 is defined in terms of applied compression and strain variance and normalized by the input signal-to-noise ratio (SNRi) for echo signals, to formulate the performance metric SNR0/SNRi. This quantity characterizes the noise properties, dynamic range, and sensitivity of strain images based on the spatial resolution requirements. The results indicate that low noise, high sensitivity, and limited dynamic range strain images are obtained for high-frequency bandpass signals when the applied strain is small. For large strains, however, one strategy for low-noise strain imaging employs base-band signals to obtain images with large dynamic range but limited peak sensitivity and noise figure. A better strategy includes companding, which eliminates the average strain in the echo signal before cross-correlation to reduce the dynamic range requirement and increase peak sensitivity for strain estimates.

Acoustics↗

PubMed1997

Statistical analysis of strain images estimated from overlapped and filtered echo signals.

The visibility of soft-tissue lesions in strain imaging is currently limited by strain noise from waveform decorrelation. Attempts to balance noise reduction with concerns for contrast and spatial resolution rely on accurate models of time delay covariance for guidance. The most useful analytical models describe the covariance of time-varying time delay estimates in terms of experimental parameters and tissue deformation patterns. Assuming compressed tissue deforms linearly along the axis of the sound beam, we derived a delay covariance expression for echo data with Gaussian spectra that were filtered by a Gaussian window function before correlation. The Gaussian filter reduced the number of assumptions needed to obtain closed-form expressions and minimized the effects of strain within the correlation window. However, strain images are often made using uniformly weighted (sinc filtered) window functions. This paper compares time delay covariances for these two window functions, and describes an equivalent window duration at which delay variances for Gaussian and uniform windows are equal. At the equivalent window length, the analysis can be used to predict strain errors for either window function. Finally, this paper uses the delay covariance data to show how strain noise and image sharpness vary depending on the amount of overlap between correlation windows. For an applied strain less than 5%, an overlap near 50% offers an adequate compromise. These results can guide the selection of experimental parameters for improving the visibility of lesions in strain images.

Acoustics↗

PubMed1996

Deformation models and correlation analysis in elastography.

Cross-correlation functions are derived with the purpose of determining how strain inhomogeneities affect the displacement estimates used in ultrasound-based elastography. Variations in the strain profile occur in most imaging situations and are caused by fluctuations in the stress field or elastic modulus of the sample. An analytical framework for developing signal processing strategies in elastography is described, and the limitations of correlation-based methods for measuring displacements in tissuelike media caused by static compression are emphasized. This paper includes (1) an accurate approximation for an inverse coordinate transformation that release pre- and postcompression reflectivity profiles of the media, (2) a derivation of the echo-signal cross-correlation function in media with deterministic or stochastic strain profiles; (3) mathematical and graphical descriptions of the consequences that nonuniformities in the strain profile impose upon the uncertainty of displacement estimation; and (4) a demonstration of the advantages of echo signal conditioning and ultrasonic-pulse shaping to reduce the nonstationary effects that attenuate the cross-correlation peak and reduce the signal-to-noise ration for displacement estimation.

Elasticity↗