Application of Adaptive Image Processing Technique to Real-Time Spatial Compound Ultrasound Imaging Improves Image Quality

Abstract

Rationale and Objectives. To assess the impact of adaptive filter postprocessing on quality of ultrasound images. Methods. Ultrasound images acquired with real-time spatial compound imaging (SonoCT imaging) were subsequently processed with an adaptive real time algorithm (XRES imaging). Conventional and XRES-processed images from abdominal, pediatric or small parts ultrasound explorations were compared. The delineation of borders, tissue contrast, amount of noise, and overall image quality were evaluated. Results. Delineation of borders and tissue contrast were improved on all images (P Ͻ 0.05). The amount of noise was reduced (P Ͻ 0.05). The overall image quality was improved for abdominal, pediatric and small parts ultrasound explorations (P Ͻ 0.05). No image degradation was found. Conclusions. Adaptive processing provided better image quality without loss of clinically useful information.Key Words: diagnostic imaging, medical electronics, image enhancement, ultrasonography (Invest Radiol 2003;38: 257-262) M any innovative technologies, such as harmonic imaging 1-4 and real-time compound imaging (SonoCT imaging), [5][6][7][8] have been introduced over the past several years to improve ultrasound (US) image quality. Real-time processing involving adaptive image analysis and enhancement (XRES imaging) is one of the latest commercially available US techniques. It derives from processing of digital signals and is based on research originally performed for use in enhancing MRI images. With this technology, the US image, initially constructed by the scan converter of the device, is further refined in real time by an adaptive algorithm prior to display on the screen.XRES imaging is considered adaptive because it adapts its processing automatically to the nature of the target, both locally (ie, within an individual image) and temporally (over time from image to image). This adaptability is achieved in XRES by having both an analysis phase, in which both real tissue structures and ultrasound artifacts are identified, and an enhancement phase, in which structures identified in the analysis phase are enhanced and artifacts are suppressed. The analysis phase of XRES takes into account many characteristics of the image, such as textural and structural properties including gradients and local statistics. The results of this analysis directly control the enhancement phase; for example, smoothing is applied along an interface to improve continuity, whereas edge enhancement is applied in the perpendicular direction to improve spatial resolution. In regions identified by the analysis phase as being relatively homogeneous (containing minimal structure or texture), smoothing is applied equally in all directions to suppress speckle and noise. Thus XRES is designed both to suppress artifacts and to enhance interfaces and margins. In addition, XRES is a multiresolution algorithm. This means that all processinganalysis and enhancement-occurs at multiple scales within the image. Multiresolution processing improves robustness by all...

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