Point detection in textured ultrasound images.

Detection of point scatterers in textured ultrasound images can be challenging. This paper investigates how four multilook methods can improve the detection. We analyze many images with known point scatterer locations and randomly textured backgrounds. The normalized matched filter (NMF) and multilook coherence factor (MLCF) methods are normalized methods that do not require any texture correction prior to detection analysis. They are especially propitious when optimal texture correction of the ultrasound images is difficult to obtain. The results show significant improvement in detection performance when the MLCF method is weighted with the prewhitened and texture corrected image. The method can be applied even when we do not have prior knowledge about the optimal prewhitening limits. The multilook methods NMF and NMF weighted (NMFW) are very favorable methods to apply on images where acoustic noise dominates the speckle background.

Point Detection in Ultrasound Using Prewhitening and Multilook Optimization.

We investigate methods to improve the detection of point scatterers in ultrasound imaging using the standard delay-and-sum (DAS) image as our starting point. An optimized whitening transform can increase the spatial resolution of the image. By splitting an image's frequency spectrum into many subsets using the multilook technique, we can exploit the coherent properties of a point scatterer. We present three new multilook methods and evaluate their effect on point detection. The performances are compared to DAS using synthetic aperture Field II simulations of a point scatterer in uniform speckle background. The results show that optimized prewhitening of the images can significantly improve the point detection. The multilook methods have the potential to improve the detection performance further when a sufficient number of looks are used. If prior knowledge about the optimal spectrum limits is unavailable and a nonoptimal prewhitening is applied, applying that the new multilook methods can considerably improve the point detection.

Detection of Point Scatterers in Medical Ultrasound.

We present an overview of the detection of point scatterers in ultrasound images and suggest strategies for evaluating and measuring the detection performance. We use synthetic aperture Field II simulations of a point scatterer in speckle background and evaluate how common imaging techniques affect point target detectability. We discuss how to compare different methods and calculate confidence intervals. In general, applying speckle reduction methods reduces the point detection performance. However, the results show that it is possible to smooth the speckle background and preserve relatively high performance with a suitable and optimized method. The different detection performances of the advanced beamforming methods coherence factor (CF), phase coherence factor (PCF), and Capon's minimum variance (MV) are presented and benchmarked with standard delay-and-sum (DAS). The results show that CF achieves slightly better detection performance than DAS for weak point scatterers, whereas PCF and MV perform worse than DAS. Choice of apodization window and adaptive aperture size affects the probability of detection. Results show that methods that preserve spatial resolution have better detection performance of point scatterers.