Elasticity imaging using conventional and high-frame rate ultrasound imaging: experimental study

High-frame rate ultrasound imaging is necessary to track fast deformation in ultrasound elasticity imaging, but the image quality may be degraded. Previously, we investigated the performance of strain imaging using numerical models of conventional and ultrafast ultrasound imaging techniques. In this paper, we performed experimental studies to quantitatively evaluate the strain images and elasticity maps obtained using conventional and high frame rate ultrasound imaging methods. The experiments were carried out using point target and tissue mimicking phantoms. The experimental results were compared with the results of numerical simulation. Our experimental studies confirm that the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and axial/lateral resolution of the displacement and strain images acquired using high-frame rate ultrasound imaging are slightly lower but comparable with those obtained using conventional imaging. Furthermore, the quality of elasticity images also exhibits similar trends. Thus, high-frame rate ultrasound imaging can be used reliably for static elasticity imaging to capture the internal tissue motion if the frame rate is critical.     

Strain imaging using conventional and ultrafast ultrasound imaging: numerical analysis

In elasticity imaging, the ultrasound frames acquired during tissue deformation are analyzed to estimate the internal displacements and strains. If the deformation rate is high, high-frame-rate imaging techniques are required to avoid the severe decorrelation between the neighboring ultrasound images. In these high-frame-rate techniques, however, the broader and less focused ultrasound beam is transmitted and, hence, the image quality is degraded. We quantitatively compared strain images obtained using conventional and ultrafast ultrasound imaging methods. The performance of the elasticity imaging was evaluated using custom-designed, numerical simulations. Our results demonstrate that signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and spatial resolutions in displacement and strain images acquired using conventional and ultrafast ultrasound imaging are comparable. This study suggests that the high-frame-rate ultrasound imaging can be reliably used in elasticity imaging if frame rate is critical     

An elasticity microscope. Part I: Methods

An elasticity microscope images tissue stiffness at fine resolution. Possible applications include dermatology, ophthalmology, pathology, and tissue engineering. In addition, if the resolution approaches cellular dimensions, then this system may be very useful in understanding tissue micromorphology. Elasticity images can be reconstructed from displacement and strain fields measured throughout the specimen during controlled external loading. High frequency ultrasound is used to obtain these images by tracking coherent speckle motion during deformation. In this paper, methods are presented to track speckle in two dimensions with near unity correlation coefficients using a high frequency, single element focused transducer. These techniques include improved means for speckle tracking. Procedures to control boundary conditions for consistent specimen deformation and scanning techniques required to obtain a plane-strain state in the imaging plane are also discussed. To test these methods, a 50 MHz elasticity microscope was constructed     

Young's modulus measurements of soft tissues with application toelasticity imaging

Ultrasound elasticity imaging is a promising method that may eventually allow early detection of many tissue pathologies. However, before elasticity imaging can be applied to its numerous potential clinical applications, the quantitative accuracy of tissue elasticity measurements must be established. Simple 1-D ultrasound elasticity measurements were performed on muscle and liver and compared with independent and established mechanical measurements to investigate both the accuracy and consistency of ultrasound elasticity measurements. In addition, some interesting properties of soft tissue and aspects of the measurement process which should be considered in elasticity measurements are discussed     

Three-dimensional motion measurements using feature tracking

Feature tracking was developed to efficiently compute motion measurements from volumetric ultrasound images. Prior studies have demonstrated the motion magnitude accuracy and computation speed of feature tracking. However, the previous feature tracking implementations were limited by performance of their calculations in rectilinear coordinates. Also, the previous feature tracking approaches did not fully explore the three dimensional (3- D) nature of volumetric image analysis or utilize the 3-D directional information from the tracking calculations. This study presents an improved feature tracking method which achieves further computation speed gains by performing all calculations in the native spherical coordinates of the 3-D ultrasound image. The novel method utilizes a statistical analysis of tracked directions of motion to achieve better rejection of false tracking matches. Results from in vitro tracking of a speckle target show that the new feature tracking method is significantly faster than correlation search and can accurately determine target motion magnitude and 3-D direction.     

Multiorgan motion tracking in dynamic magnetic resonance imaging for evaluation of pelvic system mobility and shear strain

Female pelvic disorders have a large social impact; the diagnosis of which relies on a key indication: pelvic mobility. The normal mobility is present in a healthy patient, meanwhile the hypermobility can be a sign of female pelvic prolapse and the hypomobility for endometriosis. The evaluation of pelvic mobility is based on medical image analysis. However, the latter does not provide precise values of these indicators directly. Moreover, suspension devices play an important role in pelvic organ function but can hardly be observed on medical images. Our objective is to propose an image‐based analysis tool for the quantitative evaluation of pelvic mobility and the shear strain which has an impact on suspension devices. Hence, this paper introduces a such tool based on an efficient and semiautomatic motion tracking of multiple pelvic organs: the bladder, vagina, and rectum presented in dynamic magnetic resonance imaging sequences. The method was validated on prototypical images and applied to different mobility cases. The computed displacement and shear strain fields provide important information on the quality of suspension devices between organs for a fine diagnosis in the clinical context, for example, the early diagnosis of female pelvic prolapse and the localization of possible lesion areas before surgery. Meanwhile, the predicted mobility can be used to compare with the finite element model for numerical simulation.     

Compact scanning laser ophthalmoscope with high-speed retinal tracker

The effectiveness of image stabilization with a retinal tracker in a multifunction, compact scanning laser ophthalmoscope (TSLO) was demonstrated in initial human subject tests. The retinal tracking system uses a co confocal reflectometer with a closed-loop optical servo system to lock onto features in the fundus. The system is multifarious and modular to allow configuration for many research a clinical applications. Adult volunteers were tested without mydriasis to optimize the tracking instrumentation and to characterize imaging performance. The retinal tracking system achieves a bandwidth of greater than 1 kHz, which permits tracking at rates that greatly exceed the maximum rate of motion of the human eye. The TSLO system stabilized images to an accuracy of 0.05 deg in all test subjects during ordinary saccades with a velocity up to approximately 500 deg/s. Feature lock was maintained for minutes despite subject eye blinking. Even when nearly 1000 frames were coadded, image blur was minimal. Successful frame coaddition allowed image acquisition with decreased noise in low-light applications. The retinal tracking system significantly enhances the imaging capabilities of the scanning laser ophthalmoscope.     

Heteroassociative multiple-target tracking by fringe-adjusted joint transform correlation

A heteroassociative joint transform correlation (JTC) technique is proposed for recognizing and tracking multiple heteroassociative or dissimilar targets from gray-level image sequences by use of the concept of fringe-adjusted JTC and a multiple-target-detection algorithm. A fringe-adjusted JTC technique is used to ensure quantification of the similarities among several input images while it satisfies the equal-correlation-peak criterion. Tracking is accomplished by retrieval of the target motion information estimated from multiple consecutive image frames. An enhanced version of the fringe-adjusted filter is incorporated into the heteroassociative multiple-target-detection process to optimize the correlation performance. The feasibility of the proposed technique is tested by computer simulation with real infrared image data.     

Robustness and reliability evaluations of image annotation

The semantic gap problem in image retrieval has motivated much work focusing on automatic image annotation, aimed at facilitating computers to automatically assign keywords to images. The basic measure for evaluating the annotation performance is usually to examine the annotation accuracy. To do this, the fraction of the relevant images, which have been correctly classified by a specific classifier or image annotation system, is measured. Consequently, the evaluation result can be thought of as a surrogate for the judgment of real users. However, the ability of this kind of quantitative evaluation measure to fully evaluate the performance and value of image annotation systems is limited. This paper introduces two complementary metrics related to the rates of annotation accuracy, which can help to further assess the robustness and stability of image annotation systems. They are: (i) the number of annotated keywords with zero-rate accuracy and (ii) the coefficient of variation of annotation accuracy. The evaluation results based on three datasets show that these two metrics are very useful to make a more reliable conclusion for image annotation systems.     

Cone-Beam CT with a Flat-Panel Detector: From Image Science to Image-Guided Surgery

The development of large-area flat-panel x-ray detectors (FPDs) has spurred investigation in a spectrum of advanced medical imaging applications, including tomosynthesis and cone-beam CT (CBCT). Recent research has extended image quality metrics and theoretical models to such applications, providing a quantitative foundation for the assessment of imaging performance as well as a general framework for the design, optimization, and translation of such technologies to new applications. For example, cascaded systems models of Fourier domain metrics, such as noise-equivalent quanta (NEQ), have been extended to these modalities to describe the propagation of signal and noise through the image acquisition and reconstruction chain and to quantify the factors that govern spatial resolution, image noise, and detectability. Moreover, such models have demonstrated basic agreement with human observer performance for a broad range of imaging conditions and imaging tasks. These developments in image science have formed a foundation for the knowledgeable development and translation of CBCT to new applications in image-guided interventions - for example, CBCT implemented on a mobile surgical C-arm for intraoperative 3D imaging. The ability to acquire high-quality 3D images on demand during surgical intervention overcomes conventional limitations of surgical guidance in the context of preoperative images alone. A prototype mobile C-arm developed in academic-industry partnership demonstrates CBCT with low radiation dose, sub-mm spatial resolution, and soft-tissue visibility potentially approaching that of diagnostic CT. Integration of the 3D imaging system with real-time tracking, deformable registration, endoscopic video, and 3D visualization offers a promising addition to the surgical arsenal in interventions ranging from head-and-neck / skull base surgery to spine, orthopaedic, thoracic, and abdominal surgeries. Cadaver studies show the potential for significant boosts in surgical performance under CBCT guidance, and early clinical trials demonstrate feasibility, workflow, and image quality within the surgical theatre.     

Internal displacement and strain imaging using ultrasonic speckletracking

Previous ultrasound speckle tracking methods have been extended, permitting measurement of internal displacement and strain fields over a wide dynamic range of tissue motion. The markedly increased dynamic range of this approach should lead to enhanced contrast resolution in strain and elasticity images. Results of experiments on gelatin-based, tissue equivalent phantoms show the capabilities of the method     

Theoretical analysis and verification of ultrasound displacementand strain imaging

Evaluation of internal displacement and strain distributions in tissue under externally applied forces is a necessary step in elasticity imaging. To obtain a quantitative image of the elastic modulus, strain and displacement fields must be measured with reasonable accuracy and inverted based on an accurate theoretical model of soft tissue mechanics. In this paper, results of measured internal strain and displacement fields from gel-based phantoms are compared with theoretical predictions of a linear elastic model. In addition, some aspects of elasticity reconstruction based on measured displacement and strain fields are discussed     

Quantitative 3-d diagnostic ultrasound imaging using a modified transducer array and an automated image tracking technique

An approach for acquiring dimensionally accurate three-dimensional (3-D) ultrasound data from multiple 2-D image planes is presented. This is based on the use of a modified linear-phased array comprising a central imaging array that acquires multiple, essentially parallel, 2-D slices as the transducer is translated over the tissue of interest. Small, perpendicularly oriented, tracking arrays are integrally mounted on each end of the imaging transducer. As the transducer is translated in an elevational direction with respect to the central imaging array, the images obtained by the tracking arrays remain largely coplanar. The motion between successive tracking images is determined using a minimum sum of absolute difference (MSAD) image matching technique with subpixel matching resolution. An initial phantom scanning-based test of a prototype 8 MHz array indicates that linear dimensional accuracy of 4.6% (2 /spl sigma/) is achievable. This result compares favorably with those obtained using an assumed average velocity [31.5% (2 /spl sigma/) accuracy] and using an approach based on measuring image-to-image decorrelation [8.4% (2 /spl sigma/) accuracy]. The prototype array and imaging system were also tested in a clinical environment, and early results suggest that the approach has the potential to enable a low cost, rapid, screening method for detecting carotid artery stenosis. The average time for performing a screening test for carotid stenosis was reduced from an average of 45 minutes using 2-D duplex Doppler to 12 minutes using the new 3-D scanning approach.     

An autocorrelation-based method for improvement of sub-pixel displacement estimation in ultrasound strain imaging

In ultrasound strain and elasticity imaging, an accurate and cost-effective sub-pixel displacement estimator is required because strain/elasticity imaging quality relies on the displacement SNR, which can often be higher if more computational resources are provided. In this paper, we introduce an autocorrelation-based method to cost-effectively improve subpixel displacement estimation quality. To quantitatively evaluate the performance of the autocorrelation method, simulated and tissue-mimicking phantom experiments were performed. The computational cost of the autocorrelation method is also discussed. The results of our study suggest the autocorrelation method can be used for a real-time elasticity imaging system.     

An Automatic Evaluation System for Contrast‐Detail Phantom Images in Digital Radiography

Currently, contrast‐detail phantom (CD phantom) images are widely used to assist medical experts for diagnosis, because these images can be used to study imaging quality and assess the radiation dose amount for digital X‐ray imaging systems. However, the quality of the CD phantom image varies from person to person, increasing the possibility of false diagnosis. In this article, we propose an automatic evaluation system to measure the quality of a phantom image an alternative to assessment by radiologists. The proposed method is based on bilinear pixel interpolation, geometric transformation, and region shifting to efficiently and objectively evaluate the quality of a phantom image. Moreover, misjudgment modification is also proposed to further improve the recognition accuracy. The experimental results show that the accuracy of the proposed method is very close to that of the radiologists observations. The results have also proven that the proposed method is a feasible way to evaluate the quality of a phantom image in an objective and automatic manner.     

Displacement and strain imaging of coronary arteries withintraluminal ultrasound

Tissue elasticity can be estimated from displacement and strain images acquired under controlled deformation. We extend this approach for coronary arteries, deformed and imaged by an integrated angioplasty balloon and ultrasonic imaging probe. Because the lumen cross section of a severely occluded artery is not circular, we have also developed a technique to perform all motion computations in the reference frame of the lumen's geometric center. This coordinate system is independent of the imaging catheter and consequently referencing to this frame removes artifacts associated with probe motion within the balloon during deformation. Displacements and strains estimated by phase-sensitive correlation-based speckle tracking were used to distinguish arterial plaques in simulated coronary arteries of differing elastic moduli: hard, soft, and homogenous. We have also applied these methods to images of a homogeneous gelatin phantom collected with the integrated probe. The maximum phantom displacement was about 40 pm, and the maximum radial normal strain was about 4% (absolute value). The spatial dependence of these quantities shows good agreement with theoretically predicted values     

基于变分贝叶斯多图像超分辨的平面复眼空间分辨率增强

平面复眼成像系统利用多个子孔径对场景进行成像,由于子孔径大小和图像传感器空间采样率的限制,各子孔径图像质量较差。如何融合多个子孔径图像来获得高分辨率图像是亟需解决的问题。多图像超分辨理论利用多幅具有互补信息的图像来重构高空间分辨率图像,然而现有理论通常采用过于简化的运动模型,这种简化的运动模型对平面复眼成像并不完全适用。若直接把现有多图像超分辨理论用于平面复眼分辨率增强,不准确的相对运动估计将降低图像分辨率增强性能。针对这些问题,本文在变分贝叶斯框架下改进了现有多图像超分辨理论中的运动模型,并把导出的联合估计算法用于平面复眼分辨率增强。仿真数据实验和真实复眼数据实验验证了推荐方法的正确性和有效性。     

High-resolution multiband polarization epithelial tissue imaging method by sparse representation and fusion

Multiband polarization epithelial tissue imaging is an effective tool to measure tissue's birefringence and structure for quantitative pathology analysis. To discriminate the pathology accurately, high-resolution multiband polarization images are essential. But it is difficult to acquire high-resolution polarization images because of the limitations of imaging systems. The polarization image calculation process can be regarded as image fusion with fixed rules, and multiband polarization images are intrinsically sparse. In this paper, we propose a novel high-resolution multiband polarization image calculation method by utilizing the sparse representation and image fusion method. The multiband images are first represented in the sparse domain and we further introduce total-variation-regularization terms into the sparse representation framework. Then, polarization parameter images are calculated by simultaneous fusion and reconstruction. Higher quality multiband polarization images can be obtained through additional regularization constraint in the fusion process. Extensive experiments validate that the proposed method achieves much better results than many state-of-the-art algorithms in terms of both peak signal-to-noise-ratio and visual perception.     

A Modular Software System to Assist Interpretation of Medical Images—Application to Vascular Ultrasound Images

Improvements in medical imaging technology have greatly contributed to early disease detection and diagnosis. However, the accuracy of an examination depends on both the quality of the images and the ability of the physician to interpret those images. Use of output from computerized analysis of an image may facilitate the diagnostic tasks and, potentially improve the overall interpretation of images and the subsequent patient care. In this paper, Analysis, a modular software system designed to assist interpretation of medical images, is described in detail. Analysis allows texture and motion estimation of selected regions of interest (ROIs). Texture features can be estimated using first-order statistics, second-order statistics, Laws' texture energy, neighborhood gray-tone difference matrix, gray level difference statistics, and the fractal dimension. Motion can be estimated from temporal image sequences using block matching or optical flow. Image preprocessing, manual and automatic definition of ROIs, and dimensionality reduction and clustering using fuzzy c-means, are also possible within Analysis. An important feature of Analysis is the possibility for online telecollaboration between health care professionals under a secure framework. To demonstrate the applicability and usefulness of the system in clinical practice, Analysis was applied to B-mode ultrasound images of the carotid artery. Diagnostic tasks included automatic segmentation of the arterial wall in transverse sections, selection of wall and plaque ROIs in longitudinal sections, estimation of texture features in different image areas, motion analysis of tissue ROIs, and clustering of the extracted features. It is concluded that Analysis can provide a useful platform for computerized analysis of medical images and support of diagnosis     

Uniform precision ultrasound strain imaging

Ultrasound strain imaging is becoming increasingly popular as a way to measure stiffness variation in soft tissue. Almost all techniques involve the estimation of a field of relative displacements between measurements of tissue undergoing different deformations. These estimates are often high resolution, but some form of smoothing is required to increase the precision, either by direct filtering or as part of the gradient estimation process. Such methods generate uniform resolution images, but strain quality typically varies considerably within each image, hence a trade-off is necessary between increasing precision in the low-quality regions and reducing resolution in the high-quality regions. We introduce a smoothing technique, developed from the nonparametric regression literature, which can avoid this trade-off by generating uniform precision images. In such an image, high resolution is retained in areas of high strain quality but sacrificed for the sake of increased precision in low-quality areas. We contrast the algorithm with other methods on simulated, phantom, and clinical data, for both 2-D and 3-D strain imaging. We also show how the technique can be efficiently implemented at real-time rates with realistic parameters on modest hardware. Uniform precision nonparametric regression promises to be a useful tool in ultrasound strain imaging.