Showing papers by "Johan M. Thijssen published in 1997"

Characterization of echographic image texture by cooccurrence matrix parameters

Abstract: The goal of this study was to investigate the potentials of cooccurrence matrix analysis for the characterization of echographic image texture. Echographic data were obtained by one-dimensional simulations. Various data sets were generated with different number densities of the randomly distributed scatterers and with different levels of structural scattering strength. Cooccurrence matrix parameters estimated for analysis were: angular second moment, contrast, correlation, entropy and kappa. The cooccurrence matrix analysis was tuned by varying its parameters: spatial displacement of the pixel pairs, number of gray levels and size of the window. The parameters reached a saturation level at a number density of 3-5 scatterers per resolution cell (-6 dB width). Similarly, when increasing the displacement, a limit value was reached at 4-20 samples, depending on the size of the resolution cell. Using the Mahalanobis distance as a measure of differentiating between two textures, a systematic inverse relation was observed between the size of the window and the number of gray levels used in the estimation of the cooccurrence matrix. The optimal parameters to differentiate textures without structure appeared to be entropy and angular second moment. A window size of 90 speckle cells and 64 gray levels is needed for this purpose. The effective speckle size was estimated from the mean number of maxima of the demodulated echo signals. Resolved structure results in a periodicity of parameter values with displacement. The periodicity can be calculated by changing the displacement d. Optimal parameters for detecting periodicity are contrast and correlation. Analysis of the correlation between parameters showed that entropy vs. angular second moment and contrast vs. correlation are highly correlated.

An in vivo ultrasonic model of liver parenchyma

Abstract: Several ultrasonic tissue characterization features are known to discriminate pathological from normal tissue in vivo. Previously, the authors developed an in vivo attenuation and backscatter estimation method and derived expressions predicting the standard deviation (sd) of the intercept and slope features, assuming a commonly used ultrasonic model of liver parenchyma. In its application to in vivo data the sd of the intercept features was unexpectedly high and the feature SNR (signal to-noise ratio) showed a significant bias related to the window size. In this paper, the model is extended with the notion of inhomogeneous parenchyma background (IPB). IPB is shown to be present in normal liver parenchyma and is statistically described by a noise term with small amplitude and large correlation cell size. The effect of the noise term on the features can be predicted. The results demonstrate good agreement between the estimations and predictions in in vivo data. It is concluded that IPB is a realistic and relevant phenomenon and should be part of the in vivo ultrasonic model of liver parenchyma.

Acoustic characteristics of the eye lens

Abstract: The purpose of this study is to characterize the eye lens (human and porcine) by acoustic measurements and to investigate whether relations exist with the local protein content. The acoustic measurements were performed with a ‘scanning acoustic microscope’ (SAM), operating at a frequency of 20 MHz. At this frequency the lateral resolution in the acoustic images was 150 mm. A double-transmission pulse-echo technique was employed to obtain acoustic parameter images of a central, 1-mm thick slice of the lenses. The two-dimensional images were derived by ultrasonic spectroscopy displaying the ultrasound velocity, the attenuation at 20 MHz and the slope of the attenuation coefficient between 17 and 213 MHz. The images were summarized by profiles along the optical and equatorial axes of these parameters.