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This study aims to build a deep learning (DL) architecture for automated extraction of learned-from-data image features from the shear-wave elastography (SWE), and to evaluate the DL architecture in differentiation between benign and malignant breast tumors. We construct a two-layer DL architecture for SWE feature extraction, comprised of the point-wise(More)
Ultrasound shear-wave elastography (SWE) has become a valuable tool for diagnosis of breast tumors. The purpose of this study was to quantify the elastic heterogeneity of breast tumors in SWE by using contourlet-based texture features and evaluating their diagnostic performance for classification of benign and malignant breast tumors, with pathologic(More)
Manual segmentation of ultrasound contrast images is time-consuming and inevitable to variability, and computer-based segmentation algorithms often require user interaction. This paper proposes a novel level set model for fully automated segmentation of vascular ultrasound contrast images. The initial contour of arterial boundaries is acquired based on an(More)
Supersonic shear wave imaging (SSI) has recently been explored as a technique to evaluate tissue elasticity modulus and has become a valuable tool for tumor characterization. The purpose of this study was to develop a novel computer-aided diagnosis (CAD) system that can acquire quantitative elastographic information from color SSI elastography images(More)
The first binuclear sandwich-like complexes based on the aromatic tetraatomic species with formula M(2)(η(4)-E(4))(2) (M = Al, Ga; E = N, P, As) have been studied by density functional theory (DFT). The stable conformer for each M(2)(η(4)-E(4))(2) is the staggered one with D(4d) symmetry except for Ga(2)(η(2)-N(4))(2) with C(2v) symmetry. Natural bonding(More)
PURPOSE To develop and evaluate a computer-assisted method of quantifying five-point elasticity scoring system based on ultrasound real-time elastography (RTE), for classifying benign and malignant breast lesions, with pathologic results as the reference standard. MATERIALS AND METHODS Conventional ultrasonography (US) and RTE images of 145 breast lesions(More)
Quantitatively assessing the tissue stiffness with acoustic radiation force impulse (ARFI) method has proved its worth in clinical trials. Much attention has been focused on the research of the displacement estimation algorithm in ARFI. However, the subsequent shear wave speed estimation part can also affect the accuracy and reliability of the results. In(More)
Since a key step in the analysis of gene expression data is to detect groups of genes that have similar expression patterns, clustering technique is then commonly used to analyze gene expression data. Data representation plays an important role in clustering analysis. The non-negative matrix factorization (NMF) is a widely used data representation method(More)
Acoustic radiation force impulse (ARFI) technique is a quantitative method for tissue stiffness assessment. It has been proved to be less operator dependent than the quasi-static elastography, and has more simple hardware architecture than the supersonic shearwave imaging (SSI) technique, which make it easier to be miniaturized for some special clinical(More)
Wireless capsule endoscopy has opened a new era by enabling remote diagnostic assessment of the gastrointestinal (GI) tract in a painless procedure. Video capsule endoscopy (VCE) is currently commercially available worldwide. However, it is limited to visualization of superficial tissue. Ultrasound (US) imaging is a complementary solution as it is capable(More)