Combining ADMIRE and MV to Improve Image Quality

Deconvolution based on sparsity and continuity improves the quality of ultrasound image

The application of ultrasound (US) image has been limited by its limited resolution, inherent speckle noise, and the impact of clutter and artifacts, especially in the miniaturized devices with restricted hardware conditions. In order to solve these problems, many researchers have explored a number of hardware modifications as well as algorithmic improvements, but further improvements in resolution, signal-to-noise ratio (SNR) and contrast are still needed. In this paper, a deconvolution algorithm based on sparsity and continuity (DBSC) is proposed to obtain the higher resolution, SNR, and, contrast. The algorithm begins with a relatively bold Wiener filtering for initial enhancement of image resolution in preprocessing, but it also introduces ringing noise and compromises the SNR. In further processing, the noise is suppressed based on the characteristic that the adjacent pixels of the US image are continuous as long as Nyquist sampling criterion is met, and the extraction of high-frequency information is balanced by using relatively sparse. Subsequently, the theory and experiments demonstrate that relative sparsity and continuity are general properties of US images. DBSC is compared with other deconvolution strategies through simulations and experiments, and US imaging under different transmission channels is also investigated. The final results show that the proposed method can greatly improve the resolution, as well as provide significant advantages in terms of contrast and SNR, and is also feasible in applications to devices with limited hardware.

Enhancing sizing accuracy in ultrasound images with an alternative ADMIRE model and dynamic range considerations

Ultrasound imaging can struggle with sizing accuracy, especially when the targets have a significantly different amplitude compared to the surrounding background. In this work, we consider the challenging task of accurately sizing hyperechoic structures, and specifically kidney stones, where accurate sizing is critical for determining medical intervention. AD-Ex, an extended alternative model of our aperture domain model image reconstruction (ADMIRE) pre-processing method, is introduced and is designed to improve clutter removal and improve sizing accuracy. We compare this method against other resolution enhancing methods such as minimum variance (MV) and generalized coherence factor (GCF), and against those methods using AD-Ex as a pre-processing tool. These methods are evaluated among patients with kidney stone disease, with the task of accurately sizing the stones against the gold standard, computed tomography (CT). Stone ROI's were selected using contour maps as reference from which the lateral stone size was estimated. Among the in vivo kidney stone cases we processed, AD-Ex+MV had the overall lowest sizing error among the methods, with an average error of 10.8% compared to the next best method AD-Ex which had an average error of 23.4%. For reference, DAS had an average error of 82.4%. Though dynamic range was evaluated to determine optimal thresholding for sizing applications, variability between stone cases was too high for any conclusions to be drawn at this time.

Large-Array Deep Abdominal Imaging in Fundamental and Harmonic Mode

Deep abdominal images suffer from poor diffraction-limited lateral resolution. Extending the aperture size can improve resolution. However, phase distortion and clutter can limit the benefits of larger arrays. Previous studies have explored these effects using numerical simulations, multiple transducers, and mechanically swept arrays. In this work, we used an 8.8-cm linear array transducer to investigate the effects of aperture size when imaging through the abdominal wall. We acquired channel data in fundamental and harmonic modes using five aperture sizes. To avoid motion and increase the parameter sampling, we decoded the full-synthetic aperture data and retrospectively synthesized nine apertures (2.9-8.8 cm). We imaged a wire target and a phantom through ex vivo porcine abdominal samples and scanned the livers of 13 healthy subjects. We applied bulk sound speed correction to the wire target data. Although point resolution improved from 2.12 to 0.74 mm at 10.5 cm depth, contrast resolution often degraded with aperture size. In subjects, larger apertures resulted in an average maximum contrast degradation of 5.5 dB at 9-11 cm depth. However, larger apertures often led to visual detection of vascular targets unseen with conventional apertures. An average 3.7-dB contrast improvement over fundamental mode in subjects showed that the known benefits of tissue-harmonic imaging extend to larger arrays.