the of the magnitude, i.e., intensity, of the field.) It is shown that Rayleigh statistics govern the fist-order behavior of the magnitude; and the autocorrelation of the resulting image speckle is obtained by the methodof Middleton. The corresponding power spectrum follows immediately by Fourier transformation. Theoretical and experimentally determined autocorrelation functions and power spectra derived from B-scans of a scattering phantom containing many scatterers per resolution cell are presented. These functions lead naturally to the definition of the average speckle spot or cell sue, and this inturn is comparable to the resolution cell. Each independent speckle servesas a degreeof freedom that determines the number of samples of tissue available over a target.As the speckle cell size decreases this number increases in a manner predictable from the physical parameters of the cell size. However, it is found that the speckle cellis broadened, the degrees of freedom diminished, when the object structureis correlated. This yields the possibilityof deducing information about the object structure from the second-order statistics of the speckle texture, in addition to that obtainable from the fiistorder statistics.

Statistics of Speckle in Ultrasound B-Scans

This paper reviews ultrasound segmentation methods, in a broad sense, focusing on techniques developed for medical B-mode ultrasound images. First, we present a review of articles by clinical application to highlight the approaches that have been investigated and degree of validation that has been done in different clinical domains. Then, we present a classification of methodology in terms of use of prior information. We conclude by selecting ten papers which have presented original ideas that have demonstrated particular clinical usefulness or potential specific to the ultrasound segmentation problem

/pdf/ultrasound-image-segmentation-a-survey-55ssqpzk7q.pdf

Ultrasound image segmentation: a survey

http://www.iacl.ece.jhu.edu/~prince/smia/2009/papers2009/NotxJACC05-CardiacFunction-Speckle-Tracking-Torsion.pdf

Measurement of ventricular torsion by two-dimensional ultrasound speckle tracking imaging

A method for reducing speckle noise in medical ultrasonic images is presented. It is called the adaptive weighted median filter (AWMF) and is based on the weighted median, which originates from the well-known median filter through the introduction of weight coefficients. By adjusting the weight coefficients and consequently the smoothing characteristics of the filter according to the local statistics around each point of the image, it is possible to suppress noise while edges and other important features are preserved. Application of the filter to several ultrasonic scans has shown that processing improves the detectability of small structures and subtle gray-scale variations without affecting the sharpness or anatomical information of the original image. Comparison with the pure median filter demonstrates the superiority of adaptive techniques over their space-invariant counterparts. Examples of processed images show that the AWMF preserves small details better than other nonlinear space-varying filters which offer equal noise reduction in uniform areas. >

An adaptive weighted median filter for speckle suppression in medical ultrasonic images

There is a need for noninvasive methods to detect liver steatosis, which can be a factor of liver fibrosis progression. This work aims to evaluate a novel ultrasonic controlled attenuation parameter (CAP) devised to target, specifically, liver steatosis using a sophisticated process based on vibration control transient elastography (VCTE™). CAP was first validated as an estimate of ultrasonic attenuation at 3.5 MHz using Field II simulations and tissue-mimicking phantoms. Performance of the CAP was then appraised on 115 patients, taking the histological grade of steatosis as reference. CAP was significantly correlated to steatosis (Spearman ρ = 0.81, p < 10(-16)). Area under receiver operative characteristic (ROC) curve (AUC) was equal to 0.91 and 0.95 for the detection of more than 10% and 33% of steatosis, respectively. Furthermore, results show that CAP can efficiently separate several steatosis grades. These promising results suggest that CAP is a noninvasive, immediate, objective and efficient method to detect and quantify steatosis.

Controlled Attenuation Parameter (CAP): A Novel VCTE™ Guided Ultrasonic Attenuation Measurement for the Evaluation of Hepatic Steatosis: Preliminary Study and Validation in a Cohort of Patients with Chronic Liver Disease from Various Causes

Abstruct-The first- and second-order statistics of envelope detected ultrasound (US)B-mode images for the case of a scattering phantom with many scatteiers per resolution cell have been previously derived. These characteristics are integrated over the region of a simulated focal (disk) lesion and the signal-to-noise ratio (SNR) for lesion detectability is obtained. This SNR requires the average number of independent speckle cells over the lesion area (analogous to the number of x-ray photons over the lesion area in incoherent light or x-ray imaging). This number is obtained from our autocorrelation analysis (second-order statistics). By setting the SNR expression equal to the threshold value SNRT required to detect a lesion in the presence of speckle noise, the dependence of lesion contrast on lesion diameter at threshold is found, i.e., the contrast/detail function. This is a simple inverse relation for ideal observers of US B-scans. It is also found that the contrast/detail results for envelope detectionin diagnostic ultrasound are almost identical with the results for square law detection (the usual laser case) with the latter serving as an upper limit for performance in lesion detection. Finally, the results of human observer performance using a contrast/ detail phantom are compared with the predictions for optimal or ideal 2cm Fig. 1. Schematic of contrast/detail phantom for diagnostic ultrasound. performance. The results are comparable with results for photon imaging systems, with valuesof the SNR at threshold in the neighborhood of 2-3.

Low Contrast Detectability and Contrast/Detail Analysis in Medical Ultrasound

The issue of image texture in ultrasound B-scans of soft tissue organs has become an important topic. If B-scan texture is a good descriptor of tissue parenchyma, it can be used as the basis for clinical diagnosis. Several attempts have been made to relate B-scan image textures to disease states of soft tissue.1,2,3 However, an alternative source of image texture is coherent acoustic interference, i.e. speckle, which is primarily a function of the imaging system rather than the tissue medium. Burckhardt4 first presented a simple analysis of acoustic speckle assuming many scatterers within the system resolution cell. These targets scatter wavelets with random phases. Abbott and Thurstone5reviewed the difference between traditional laser speckle and broadband pulse echo acoustic speckle in images of diffuse structures. Bamber and Dickinson have developed a computerized tissue model6 and have made statistical measurements of texture from simulated B-scans based on that model.7 Flax et al. have also recently shown results from numerical modeling and measurements of B-scan image texture.8

J.M. Sandrik

Papers

Statistics of Speckle in Ultrasound B-Scans

Low Contrast Detectability and Contrast/Detail Analysis in Medical Ultrasound

Measurements and analysis of speckle in ultrasound b-scans