Showing papers in "Ultrasonic Imaging in 2020"

TL;DR: This study investigates the feasibility of using three published convolution neural network models built for optical flow by the computer vision community for breast ultrasound strain elastography with significant improvements due to retraining, and finds that the PWC-Net model was the best neural network model for data investigated.

TL;DR: Deep learning with CNNs exhibited equal or higher AUC compared with radiologists when discriminating benign from malignant breast masses on ultrasound SWE.

TL;DR: The bounding box significantly improved the performance of the networks with U-Net Dice coefficients of 0.48 for automatic and 0.83 for semi-automatic segmentation of plaque when compared to manual segmentations of the same plaque by an experienced sonographer.

TL;DR: In this article, the nature of ultrasound speckle patterns from soft vascularized tissues was investigated and some open questions about their nature were raised about the nature and nature of these patterns.

TL;DR: The proposed method is of practical significance in assisting doctors to detect breast lesions, and provides some practical and theoretical support for the development and engineering of intelligent equipment based on artificial intelligence algorithms.

TL;DR: A new method based on the signal-to-noise ratio (SNR) among the element echo signals was developed for enhancement of the effect of the coherence factor (CF), which was previously developed for improvement in spatial resolution and contrast.

TL;DR: The study showed that the areas under the ROC curve for radial edge, low perfusion and IMAX for the luminal epithelium subtype breast lesions were 76.5%, 75.6%, and 82.1%, respectively.

TL;DR: The theoretical background and algorithms for liver fibrosis assessment by ultrasound backscatter envelope statistics parametric imaging were presented, and the specific applications of ultrasound back scatter envelopeStatistics parametric Imaging techniques to liver Fibrosis evaluation were reviewed and analyzed.

TL;DR: The USIE could be a new method for the evaluation of skeletal muscle fatigue state through changes in the ultrasound image entropy (USIE) during the fatigue process.

TL;DR: The proposed enhancement method is based on scaling with neutrosophic similarity score (NSS) and outperformed the other methods in terms of mean brightness preservation, edge preservation, structural similarity, and human perception-based image quality assessment.

TL;DR: A fully automatic method, based on an improved Otsu’s method and an adaptive wind-driven optimization technique, is proposed for estimating the intima media thickness of the common carotid artery and it is concluded that the proposed method has strong robustness and can provide accurate IMT estimations.

TL;DR: Although both machine learning models differentiate between healthy trapezius muscle and that of patients with FM, only the SVM model demonstrated clinically relevant performance levels.

TL;DR: The qualitative and quantitative evaluations of 2D and 3D data demonstrate that in the proposed method, which uses the spatial and temporal relation of RF images and the MC theory, the reconstruction is more accurate, and the reconstruction error is lower.

TL;DR: A noninvasive method that can be used to quantify liver stiffness using quasi-static ultrasound elastography approach is evaluated and suggested that the intra- and interoperator reproducibility of the liver elasticity also improved when using the handheld device.

TL;DR: The S_CEEMDAN method provides improved harmonic images owing to its good adaptivity and lower motion artifacts, and is thus a potential alternative to the current methods for ultrasonic harmonic imaging.

TL;DR: A cross-correlation (CC)-based method for automated IVC movement tracking and measurement, which requires minimal manual input and avoids manual selection of reference markers is developed, serving as an alternative to traditional IVC measurement.

TL;DR: The results demonstrate an additional advantage of having larger field of view for the ABT method compared with spatial compounding approach, and the contrast-to-noise ratio (CNR) estimated from rotation elastogram obtained using ABt method is better by 300% and 35% compared with that obtained by using CLA and SDC methods, respectively.

TL;DR: In this article, a cost-effective and non-invasive imaging technique, which can be used to reconstruct mechanical parameters of tissues such as Young's modulus, Poisson's ratio, inters...

TL;DR: The study indicates that imaging of compressible inclusions may benefit from targeted B-mode image forming algorithms, and its modeling framework can potentially be useful in differentiating hard inclusions from surrounding parenchyma, and for classifying kidney stones or gallstones.

TL;DR: The goal of this technique is to map defects in the diffuse regime rather than to develop a conventional image, and contrast ratios in the resulting images were in good agreement with scattering concentrations in phantom studies.