Image Understanding Research Papers - Academia.edu (original) (raw)

We present an enhanced block matching approach to improve displacement accuracy in ultrasound sequences using a combination of matching measures. The first measure uses the normalised cross correlation for regions of strong signal and the second measure CD , specifically for regions of speckle determined by the speckle signal to noise ratio. We also show displacement field results for simulated speckle and in vitro data. With modern ultrasound machines providing realtime sequence digitisation, motion estimation research in this area for noise filtering, tracking and registration has increased. In this paper we investigate a novel practical alternative to elastography using speckle tracking to infer tissue motion. Our contribution includes applying two speckle pattern similarity measures, adapting to regions of varying signal and noise within a multiresolution framework with displacement processing. We focus on synthetic and in vitro interframe and trajectory displacement accuracy. Scatter occurs when small imperfections (scatterers) cause seemingly random reflections and refractions of the sound wave. Scatterers account for a decrease in image quality, causing blurring and decreased intensity at impedance boundaries, while within the medium they create speckle. The statistics of the signal depends on the density of scatterers, with a large number of randomly located scatterers following a Rayleigh distribution (fully developed speckle). These conditions are seldom met, resulting in different statistical speckle models being used. Using B-mode images 2D tissue motion can be measured by tracking the movement of the speckle produced by the back scattering of the ultrasound itself. To date, the most popular approaches to speckle tracking use 2D region-based matching that assumes the optical flo w is constant over a defined region, for example (1), favouring normalised cross correlation (NCC) compared to other matching criteria, and optical flo w to estimate tissue motion. Cohen and Dinstein (2) and Boukerroui et al. (3) use an alternative speckle matching measure (CD ), that assumes the speckle patterns in ultrasound images can be represented by a multiplicative Rayleigh distributed noise. In our recent work (4) accurate interframe displacements and motion trajectories of individually tracked blocks were reported, using hierarchical blocks and a multiple scale NCC similarity measure. Focusing on musculoskele- tal ultrasound, in deeper body regions a general reduction in correlation as a result of increased speckle noise was observed, affecting the correlation measure. Here, by combining two matching measures, we aim to maintain ac- curacy in strong signal regions using the first measure NCC, with low correlation and a low speckle signal to noise ratio (SNR) indicating necessary re-tracking using the second measure CD . In this work, we favour displacement estimation with displacement post-processing, rather than speckle filter pre- processing and then displacement estimation. Although much research has been aimed at removing speckle to enhance ultrasound image understanding, many schemes produce increasingly homogeneous regions. This is due to features that are the same scale as the speckle being eliminated (5) impeding local motion estimation. Filter performance tends to be measured by quantifying edges and boundaries, with speckle preservation and fluctuation reduction measured using the co-occurrence matrix and localised mean and standard deviation (speckle SNR). In our situation all echo information is maintained, justifying a region-based motion estimation approach that has some inherent robustness to speckle incoherence and machine noise for speckle tracking. Although substantial research exists using low frequencies at MHz (abdominal (2), cardiac and breast (3)), we focus on higher frequencies MHz for musculoskeletal diagnosis, capturing higher resolution images at a reduced penetration depth. This is due to attenuation where the signal is reduced by approximately dB/cm/MHz (6). We used three different probes (with bandwidths , and MHz), to capture perfect conditions of an in vitro tendon section in a still water bath with clamped probe, and normal conditions of an in vivo freehand scanning of muscle. Sequences captured with perfect conditions were temporally stable resulting in high tracking