Quantitative Analysis of Ultrasonic B-Mode Images

Abstract

Various sources of variability, such as speckle noise, depth dependence and inhomogeneous intervening tissue, are involved in B-mode images, even when using the same ultrasonic equipment with fixed settings. The behavior of these sources of variability was investigated by texture analysis of images obtained from simulations and from a tissue-mimicking phantom, a normal adult liver and a pediatric renal (Wilms') tumor. First-order statistics (MEAN and SNR) and second-order statistics from the co-occurrence matrix (ENT and COR) were calculated. In a phantom, the SNR and ENT show a clear depth dependence. In biological tissue, the variability is mainly caused by the speckle noise and inhomogeneous intervening tissue. In addition, almost the entire range of the COR feature is present in images of liver and tumor. Furthermore, all the features calculated in windows of 1 cm² exhibit an overlap among the different media. With the second-order features, it is possible to discriminate 85% reliable (average) between the normal, adult, liver and the pediatric renal tumor above a window size of 9 cm². The SNR can not discriminate between these tissues. The maximum resolution of 9 cm² reveals a serious limitation of parametric imaging. Finally, the features reproduce well in the case of follow-up of an abdominal tumor during chemotherapy.

Keywords

Co-occurrence matrix liver texture tissue mimicking phantom ultrasound Wilms'tumor

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