Improvement of lesion detection by echographic image processing: Signal-to-noise-ratio imaging

Abstract

Signal-to-noise-ratio (SNR) images were constructed by a sliding window technique. Theoretical derivations of the first order statistical properties of SNR images are given for the case of intensity coding of the original images for low number densities and for the limit case of fully developed speckle. The original images were obtained by realistic simulations of backscattering by homogeneous media, while using a range of number densities of the scatterers (isotropic scattering). The SNR imaging method is illustrated by results obtained from simulated scattering media containing a lesion that is contrasting in reflectivity level or in number density of the scatterers. A considerable improvement in lesion detection is obtained if the primary difference from the background speckle is due to a different number density of the scatterers within the lesion.

An in vivo ultrasonic model of liver parenchyma

“…Although the approximation looks rather poor, it does produce good predictions. For example, the SD of the average value is predicted by (20) and can use either (10) or the approximation (13). With the in vivo parameters, it can be shown that the two predicted SDs are nearly identical in the window size range used in this study.…”

“…Even without IPB there already is a window size dependence, because in windows in the order of the speckle size the correlation between pixels tends to underestimate s w , which results in an increased SNR. This relation is well known [20], [21]. The relation between window size and expected SNR in the presence of IPB is derived in the Appendix.…”

“…where (20) or (21) can be used to estimate σ 2 v ; and (26) assumes that the variance due to IPB is uncorrelated to the mean, which is plausible as they are the result of different processes. In 1988 Dr. Thijssen received the pioneer award of the world Federation for Ultrasound in Medicine and Biology.…”

Segmentation of the Heart Muscle in 3-D Pediatric Echocardiographic Images

“…Adaptive filtering might be based on the original B-mode gray level images, but various other gray level encodings have also been tried. Local first-order and second-order statistical parameters that were used are: mean (Bamber and Daft 1986), median (Loupas et al 1989), signal-to-noise ratio (inverse of the coefficient of variation; Verhoeven et al (1991), root-mean-squares (Kotropoulos and Pitas 1992) and mean squares (this paper). For a general assessment of adaptive filtering see Verhoeven and Thijssen (1993).…”

Three-dimensional segmentation of the heart muscle using image statistics

“…Local first order and second order statistical parameters that were used are: mean 14 , median 15 , signal-tonoise ratio (inverse of coefficient of variation 16 ), root-mean-squares 17 , mean squares (this paper). See for a general assessment of adaptive filtering.…”