A method for vector displacement estimation with ultrasound imaging and its application for thyroid nodular disease.
ABSTRACT Ultrasound elastography is a promising imaging technique that can assist in diagnosis of thyroid cancer. However, the complexity of the tissue movements under freehand compression requires the use of a parametric displacement model and a specific estimation method adapted to sub-pixel motion. Therefore, the aim of this study was to develop a motion estimation method for ultrasound elastography and test its performances compared to a classical block matching technique. The proposed method, referred to as Bilinear Deformable Block Matching (BDBM), uses a bilinear model with eight parameters for controlling the local mesh deformation. In addition, a technique of motion initialization based on a triangle scan of the images adapted to ultrasound elastography is proposed. The BDBM method includes an iterative multi-scale process. This iterative approach is shown to decrease the absolute error of the displacement estimation by a factor of 1.4 when passing from 1 to 2 iterations. The method was tested on simulated images and the results show that absolute displacement estimation error was reduced by a factor of 4 compared to classical block matching. We applied the BDBM method on three experimental sets of data. In the first data set, a phantom designed for ultrasound elastography was used. The two other sets of data involve the thyroid gland and were acquired using freehand tissue compression by ultrasound probe of a clinical ultrasound scanner modified for research. A similarity measurement based on local cross-correlation shows that, for experimental data, the BDBM method outperforms the usual block matching.
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ABSTRACT: Arterial motion estimation in ultrasound (US) sequences is a hard task due to noise and discontinuities in the signal derived from US artifacts. Characterizing the mechanical properties of the artery is a promising novel imaging technique to diagnose various cardiovascular pathologies and a new way of obtaining relevant clinical information, such as determining the absence of dicrotic peak, estimating the Augmentation Index (AIx), the arterial pressure or the arterial stiffness. One of the advantages of using US imaging is the non-invasive nature of the technique unlike Intra Vascular Ultra Sound (IVUS) or angiography invasive techniques, plus the relative low cost of the US units. In this paper, we propose a semi rigid deformable method based on Soft Bodies dynamics realized by a hybrid motion approach based on cross-correlation and optical flow methods to quantify the elasticity of the artery. We evaluate and compare different techniques (for instance optical flow methods) on which our approach is based. The goal of this comparative study is to identify the best model to be used and the impact of the accuracy of these different stages in the proposed method. To this end, an exhaustive assessment has been conducted in order to decide which model is the most appropriate for registering the variation of the arterial diameter over time. Our experiments involved a total of 1620 evaluations within nine simulated sequences of 84 frames each and the estimation of four error metrics. We conclude that our proposed approach obtains approximately 2.5 times higher accuracy than conventional state-of-the-art techniques.Sensors (Basel, Switzerland). 01/2014; 14(6):9429-50.
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ABSTRACT: In this paper, a 2D least square FIR differentiation filter method is proposed in the context of tensorial elastography. Displacements are estimated from ultrasonic images obtained during freehand compression. Two 2D filters are used for providing all partial derivative maps according to the estimated motion obtained with a Bilinear Deformable Block Matching method. From these results, several strain tensor images are built, revealing the tissue’s elasticity properties. Among these tensors, the infinitesimal strains, the rigid rotation and principal strains tensors are retained, thus improving the contrast between the tumor and the background tissue. The 2D filters were first applied to displacement maps estimated from simulated data and two experimental RF data sets and then compared to the 1D differentiation filter LSQSE used in elastography. The first experimental data set was collected from a homogeneous phantom with a cylindrical hard inclusion and the second data set was collected from a thyroid gland with a malignant tumor. For all studied RF data sets, the contrast between the tumor and the background tissue calculated on strain tensor maps was increased up to a factor of 3 with our method compared to the LSQSE method. We also observed that the rigid rotation tensor and principal strains tensor were well adapted to thyroid elastography.01/2010;
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ABSTRACT: OBJECTIVE. The aim of this systematic review was to determine the diagnostic accuracy of sonoelastography in detecting malignant thyroid nodules. MATERIALS AND METHODS. A systematic search in MEDLINE and bibliographic databases was performed for the terms "thyroid nodule" and "sonoelastography." The inclusion criteria were the report of a 4- or 5-point scoring scale for elasticity score by qualitative sonoelastography as the index test and fine-needle aspiration (FNA) cytology or histopathology for thyroid nodules as the reference standard. Studies in which only the strain ratio was reported and studies of patients with underlying medical conditions were excluded. The methodologic quality of the studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool. A meta-analysis of diagnostic accuracy measures for sonoelastography was performed using Meta-DiSc freeware software (version 1.4). RESULTS. A total of 12 studies assessing 1180 thyroid nodules (817 benign and 363 malignant) were included. The most commonly used threshold for characterizing malignancy-that is, elasticity scores between 2 and 3-showed a sensitivity of 86.0% (95% CI, 81.9-89.4%) and specificity of 66.7% (95% CI, 63.4-69.9%) with positive and negative likelihood ratios and a diagnostic odds ratio of 3.82 (95% CI, 2.38-6.13), 0.16 (95% CI, 0.08-0.32), and 27.51 (95% CI, 9.21-82.18), respectively. The highest sensitivity of the test was achieved by a threshold elasticity score of between 1 and 2 with a sensitivity of 98.3% (95% CI, 96.2-99.5%). CONCLUSION. Sonoelastography can be considered as a reliable screening tool for characterizing thyroid nodules. An elasticity score of 1 is indicative of benign pathology in almost all cases and can be used to exclude many patients from further invasive assessments.American Journal of Roentgenology 04/2014; 202(4):W379-89. · 2.90 Impact Factor