Thesis (MTech (Radiography))--Cape Peninsula University of Technology, 2006. / The knee is one of the most complicated joints in the body. The deep infrapatellar bursa being only a small water-pocket and forming a small part of the knee. The deep infrapatellar bursa can get inflamed and cause great discomfort, especially to professional sportsmen and -women. If such a inflammation is present, a common treament option are to inject a cortisone solution into the bursa for quick relieve and healing. This study was performed to investigate the specific ultrasound features of a normal deep infrapatellar bursa. Thus enableing more specific and accurate diagnosis of deep infrapatellar bursitis or not, which in turn leads to quicker recovery of the patients.

Thesis: B.S., Massachusetts Institute of Technology, Department of Biology, 1976 / Includes bibliographical references. / by Ann B. Mansfield. / B.S. / B.S. Massachusetts Institute of Technology, Department of Biology

Breast cancer is the most common cancer in women, accounting for almost one-thirdof new cancer diagnoses in the United States. The mortality rate has decreased by 42% since 1989 due to early diagnosis, improvements in imaging techniques and treatment regimens. Despite all the advances in imaging modalities, there is still a need for a non-invasive, nonionizing, and low-cost diagnosis technique with high sensitivity and specificity to reduce the rate of invasive biopsies. For individuals diagnosed with locally advanced breast cancer and early-stage breast cancer, neoadjuvant chemotherapy (NACT) has become the standard of care. Pathologic complete response (pCR) is the ideal outcome of NACT, which is correlated with the prognosis and overall survival of the patients. The pCR is achieved in only about 15-20% of patients determined at the time of surgery; therefore, most patients receive a treatment that is not beneficial for them and has considerable side effects. Thus, early detection and monitoring of breast tumor response to NACT is critical for treatment planning and improving overall survival. Ultrasound-based elasticity imaging techniques have gained interest in the clinic due to their potential to provide qualitative and/or quantitative information about tissue stiffness, which is presently not unachievable with standard ultrasonography. These techniques rely on the fact that a breast tumor’s stiffness or Young’s modulus is higher than that of the surrounding normal tissues. In this dissertation, the clinical feasibility of a technique called harmonic motion imaging (HMI) for breast tumor classification, as well as for NACT response prediction and monitoring of solid tumors is investigated. HMI is an ultrasound-based elasticity imaging technique that evaluates the mechanical properties of the underlying tissues by inducing amplitude modulated (AM) displacements at a specific frequency. First, we investigated whether HMI can characterize and differentiate human breast tumors based on their relative stiffness. We enrolled female patients with benign and malignant tumors and imaged them with a clinical HMI system. The malignant tumors were found to be associated with lower HMI displacements or higher stiffness than the benign tumors. Then, in order to verify our clinical findings, we estimated HMI displacements in the postsurgical breast specimens from the same subjects and compared them against the in-vivo estimations. Our findings indicated that HMI successfully differentiated tumors from the surrounding tissue in both ex-vivo and in-vivo conditions, with an excellent correlation between the results in the two different settings. Second, we introduced and characterized a new HMI setup consisted of a multi-element focused ultrasound transducer (FUS) with electronic beam steering capability. Therefore, instead of mechanical translation of the HMI setup, the acoustic force could be electronically steered in the volumetric space to accelerate the data acquisition. A pulse sequence was developed to drive the HMI transducers assembly, the FUS and imaging transducer, using a single ultrasound data acquisition system to have a compact setup that is more applicable for clinical settings. The data acquisition was further improved by investigating the effect of AM frequencies on the quality of the HMI images and tumor detection. We found that higher AM frequencies are needed in order to improve the detection and characterization of small and stiff inclusions. On the contrary, soft and large inclusions are better resolved at lower AM frequencies. Lastly, we investigated the feasibility of using HMI for early prediction of response to neoadjuvant chemotherapy in cancer mouse models and breast cancer patients. We acquired longitudinal HMI images from pancreatic and breast cancer murine tumors during treatment with chemotherapeutic drugs and monitored the changes in the mechanical properties of the tumors. The tumors were found to soften when responsive to treatment, followed by the stiffness increase in the case of drug resistance. However, the untreated mice underwent steady stiffening of the tumors. Next, we imaged breast cancer patients at different timepoints during their chemotherapy treatment. We found that tumors in the patients who achieved pCR had higher pre-treatment stiffness and higher softening from pre-treatment to a short-interval follow-up on treatment compared to the ones in patients with residual cancer cells at the completion of treatment. These findings indicate the promising potential of HMI in the early prediction of solid tumor response to chemotherapy interventions.

No description available.

Heart disease remains the leading cause of death globally, and prevalence has nearly doubled over the past three decades. It is estimated that up to 90% of cardiovascular events are preventable, but early detection and treatment is crucial. In this dissertation, we report on the optimization of the ultrasound-based cardiac strain imaging technique known as Myocardial Elastography (ME), a method for the detection of the most common and most lethal forms of heart disease: Coronary Artery Disease (CAD) which affects the major coronary arteries, and Coronary Microvascular Disease (CMD) which affects smaller coronary vessels. CAD has historically been the primary focus of clinical cardiac imaging, whereas CMD has been under-diagnosed due to a lack of awareness and challenges associated with imaging at the microvascular level. Ultrasound-based cardiac strain imaging has been shown capable of detecting functional changes due to CAD and may be effective in CMD detection, although the latter has not yet been sufficiently investigated. However, the diagnostic accuracy of strain imaging is reduced by noise from transcostal imaging, known as clutter, and by the limited lateral resolution of high framerate ultrasound. These factors preclude accurate strain imaging in up to 30% of patients. Myocardial elastography is a precise high framerate strain imaging technique that analyzes radiofrequency (RF) signals to quantify myocardial deformation. We hypothesize that ME can effectively image and diagnose the functional effects of CMD and CAD, and that novel beamforming and clutter-filtering techniques can improve ME imaging and strain estimation quality, thereby increasing diagnostic accuracy. To improve disease detection, Stress ME (S-ME) was proposed as a method to compare strain measurements at rest to strain during induced cardiac stress. A novel strain difference (Δ𝜺) metric was presented and investigated in a canine model of induced acute ischemia, as well as in a human CAD patient study with validation by myocardial perfusion imaging. In the canine model, flow-limiting stenosis was induced by partial ligation in N=2 canines, and stenosis was found to significantly reduce Δ𝜺 in the affected myocardial regions. In the clinical study, radial and circumferential ME strain and radial Δ𝜺 was measured in N=49 myocardial segments from 8 patients suspected to have ischemia or infarction due to CAD. The median Δ?, radial strain, and circumferential strain magnitudes were lowest in infarcted regions and highest in regions with normal perfusion, while measurements in ischemic regions fell in between. ROC analysis of radial strain metrics revealed that Δ𝜺 had the highest AUC for detecting ischemia (AUC=0.788 p<0.01) and infarction (AUC=0.792, p<0.05), followed by radial strain during stress (ischemia AUC=0.774 p<0.05, infarct AUC=0.758 p<0.05) while the AUC was lowest when considering only the radial strain at rest (ischemia AUC=0.52 p>0.05, infarct AUC=0.58 p>0.05). The results thus indicate that S-ME may improve detection of mild CAD cases that are functionally asymptomatic at rest. Despite these promising findings, accurate strain imaging remains hindered by clutter noise and poor image quality. Two complementary techniques were thus developed to improve image quality and strain estimation in high frame rate cardiac strain imaging; a novel Sliding Window implementation of the Minimum Variance beamformer (SWMV) was proposed to enhance speckle quality, while a spatiotemporal singular value decomposition filter (SVD) was developed to increase tissue visibility and contrast by suppressing static clutter signals using automated cutoff selection. SWMV and SVD were shown to effectively improve image quality in simulation studies and phantom imaging experiments. In vivo performance evaluation consisted of applying SWMV beamforming and SVD filtering techniques to a dataset of N=70 strain images from 13 patients suspected to have CAD. CCTA imaging was used for validation of strain estimation. Tracking was improved in 92% of cases with a median improvement of 15% in displacement estimation accuracy as evaluated by an intersection-over-union (IoU) metric. The proposed techniques also improve agreement with CCTA results; ROC analysis shows improved AUC with SWMV+SVD compared to DAS when comparing healthy regions to those with any degree of stenosis (AUC 0.64 vs 0.56) as well as when comparing healthy to severely stenosed regions (AUC 0.69 vs 0.60). The observed results point to significant improvement in strain estimation reliability due to SWMV beamforming combined with SVD processing. The final aim and the overarching goal of this work is a culmination of the previous sections for a clinical evaluation of ME as a diagnostic tool for CAD and CMD. In this clinical study, the enhanced ME technique utilizing SWMV and SVD filtering was applied to a cohort of N=201 patients with suspected coronary disease. All patients underwent invasive angiography or noninvasive cardiac imaging in the form of coronary computed tomography or nuclear stress testing. In addition, demographic information and patient clinical history were collected and accounted for in a multivariate statistical analysis. A K-nearest-neighbor (KNN) classifier was trained to distinguish between healthy and stenosed myocardial regions, and achieved an AUC of 0.91, with sensitivity of 86% and a specificity of 85% after training with 10-fold cross validation. CMD was also shown to significantly reduce regional strain measurements. This retrospective study identified the clinical factors which impact strain, and assessed the potential advantages of incorporating ME imaging to the existing clinical imaging pipeline for CAD and CMD diagnosis.

published_or_final_version / Electrical and Electronic Engineering / Master / Master of Philosophy

Diagnoses using images made with non-ionizing ultrasound are based on qualitive criteria and are not more accurate than those made with mammography. Information about tissue state is lost in the processing required to produce ultrasound images, and textural information may not be perceptible to a human observer. This study uses statistical pattern recognition to classify ultrasound A-scans, before any processing other than amplification occurs. A U. I. Octoson was used to collect data from normal, benign, and malignant, in vivo breast tissues. Features based on textural or frequency content of received sound were computed from digitized A-scans. Most textural features have been used previously in image processing, while frequency features assumed differences in frequency-dependent attenuation. Data were collected at the University of Arizona from 17 malignant masses, 8 benign masses, and 7 normal tissues. Univariate and multivariate statistical tests were used to find combinations of features which discriminated best between the classes of tissue. Equal a priori probabilities were used in a Bayesian classifier to classify malignant vs. nonmalignant. Specificity of 76% (13 of 17 malignant masses correct) was found with a sensitivity of 80% (12 of 15 masses correct). A linear combination of one frequency feature and three textural features was used. For malignant vs. benign, sensitivity of 88% (15 of 17 masses) and specificity of 75% (6 of 8 masses) were found. Features used were the same as for classification of malignant vs. nonmalignant, except for modification of one textural feature. The inability to visually detect and gather data from some palpable masses means that further study is needed to determine the effectiveness of applying the method to all breast masses. A set of A-scans from Thomas Jefferson Hospital in Philadelphia was gathered using similar procedures, and analysed with the following results: 18 of 21 (86%) malignant masses, and 45 of 66 (68%) nonmalignant masses were classified correctly, using a linear combination of one textural feature and five frequency features. Confidence limits on the results show that the majority of masses can be classified correctly with this procedure, but success rates are not high enough for breast cancer screening.

Thesis submitted in full compliance with the requirements for the Masters in Technology Degree: Radiography, Durban University of Technology, 2006. / This study aimed at determining and evaluating the prevalence of gallstones in the Black population of District 28 (D28) in relation to age, gender, diet and body mass index (BMI) in order to identify people at high risk and advise them so that they can avoid the complications and decrease the morbidity rate. Blacks are thought to have increased prevalence of gallstones but there has been no systematic evaluation of its prevalence in D28. METHODS AND MATERIALS 389 Black people from D28 were selected from referrals (for many different radiological examinations) coming to the X-ray and ultrasound departments. Some of the respondents were staff members who also met the selection criteria for the study. An interview was conducted at Ngwelezane hospital using a structured questionnaire on health, social and diet history of the respondents. All information was entered into the data sheet. All respondents were then scanned using Mid-range ultrasound machines to establish the presence of gallstones and this information was thereafter documented on the data sheet. SPSS version 11.5 (SPSS Inc, Chicago, III) was used for data analysis. Prevalence and 95% confidence intervals were calculated using the Epitable module of Epi Info version 6.04 (CDC, 2001). Pearson's Chi square tests were used to assess associations between categorical variables and gall stones. Logistic regression analysis was applied to assess the independent effects of multiple risk factors on the development of gallstones. Backwards elimination method based on likelihood ratios was used with entry and exit probabilities set at 0.05 and 0.1 respectively / M

由線性彈性模型引起的多維系數反問題在很多範疇都有其應用，如斷層探測、油田檢測、鹽石檢測、礦石檢測及醫療成像等。瞬時成像技術是其中最有用的應用。它提供了一個快速及安全的醫療成像技術，可以用來檢測在身體內快速移動的器官的一些異常組織，如肝腫瘤。在這篇論文中，我們會重點討論兩個解決瞬時弹性成像反問題的數值方法，即水平集反演方法和近似全局收斂方法。我們會研究這兩種方法的推導和數值結果。 / 特別地，近似全局收斂方法是一種由Klibanov 新提出用來解決由雙曲偏微分引起的多維系數反問題的方法。因為這佪方法沒有使用求泛函極小值的步驟，因此能避免了一些眾所周知的問題，所以它特別穩定。數值結果顯示近似全局收斂方法對噪聲有很高的穩定性。這表明近似全局收斂方法是一個解決由線性彈性模型引起的多維系數反問題的其中一個有效方法。 / Multi-dimensional coefficient inverse problem (MCIP) in linear elasticity has found many applications, such as crack detection, oil/salt/ore detection, medical imaging. Transient elastography is among one of the most useful applications, providing a fast and safe medical imaging technique which can be used to detect tumors or abnormal tissue in “fast-moving“ organs such as the liver. In this thesis focus is casted on two of the numerical algorithms to solve inverse problems related to transient elastography, namely the level-set inversion method and the approximate globally convergent method. The derivations of both methods and numerical results are presented. In particular, the approximate globally convergent method is a newly developed stable method to solve coefficient determination inverse problem for hyperbolic partial differential equation proposed by Beilina and Klibanov in [6]. It achieves pproximately a global convergence by avoiding construction of a least squares functional, thus averting some of the well-known problems of trapping in the neighborhoods of local minima when one minimizes such a nonlinear functional. The results of the approximate globally convergent method have shown its strong stability and robustness. This suggests a good way for the reconstruction of the distribution of the shear modulus in the coefficient inverse problem of linear elasticity. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Chow, Yat Tin. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2012. / Includes bibliographical references (leaves 98-102). / Abstracts also in Chinese. / Chapter 1 --- Introduction --- p.6 / Chapter 2 --- Linear Elasticity Model --- p.9 / Chapter 2.1 --- Introduction to Linear Elasticity Model --- p.9 / Chapter 2.2 --- Physical Meanings of Elasticity Equation --- p.12 / Chapter 2.3 --- Derivations of Linear Elasticity Equation --- p.14 / Chapter 2.4 --- Discussion of Christoffel’s Equation --- p.17 / Chapter 3 --- Formulations of the Forward and Inverse Problem --- p.27 / Chapter 3.1 --- The Forward Problem --- p.29 / Chapter 3.2 --- The Inverse Problem --- p.29 / Chapter 3.3 --- A Uniqueness Result --- p.30 / Chapter 4 --- Algorithms for Inverse Problems in Elasticity --- p.33 / Chapter 5 --- Level Set Inversion Method --- p.37 / Chapter 5.1 --- Arrival Time Acquisition: Cross-Correlation --- p.37 / Chapter 5.2 --- The Distance Inversion Method --- p.41 / Chapter 5.3 --- Solving the Forward Eikonal Equation --- p.43 / Chapter 5.3.1 --- Discretizing the eikonal equation --- p.43 / Chapter 5.3.2 --- A forward eikonal solver: fast marching algorithm --- p.47 / Chapter 5.3.3 --- A forward eikonal solver: fast sweeping algorithm --- p.50 / Chapter 5.4 --- Level Set Inversion Scheme --- p.54 / Chapter 5.5 --- Numerical Implementation --- p.57 / Chapter 5.6 --- Results of Reconstructions --- p.58 / Chapter 6 --- Approximate Globally Convergent Method --- p.63 / Chapter 6.1 --- The Forward Problem --- p.65 / Chapter 6.1.1 --- Forward problem in time domain --- p.65 / Chapter 6.1.2 --- Forward problem in Laplace domain --- p.67 / Chapter 6.2 --- The Inverse Problem --- p.67 / Chapter 6.2.1 --- Inverse problem in time domain --- p.67 / Chapter 6.2.2 --- Inverse problem in Laplace domain --- p.68 / Chapter 6.3 --- A Nonlinear Integral Differential Equation --- p.69 / Chapter 6.4 --- Approximation of the First Tail --- p.71 / Chapter 6.5 --- The Algorithm --- p.72 / Chapter 6.6 --- Notes About the Convergence Analysis --- p.76 / Chapter 6.6.1 --- Approximate global convergence --- p.76 / Chapter 6.6.2 --- Basic formulation of Theorem 2.9.4 of [6] --- p.78 / Chapter 6.6.3 --- Some ideas of the convergence analysis for the algorithm in section 6.5 --- p.80 / Chapter 6.7 --- Numerical Implementation --- p.81 / Chapter 6.8 --- Results of Reconstructions --- p.88 / Chapter 7 --- Conclusions --- p.96 / Bibliography --- p.98

在各种临床应用广泛使用的诊断和治疗工具中，超声成像是其中的一个。与其他成像模式相比，比如计算机断层照相法和磁共振成像，超声波检查法有许多优点:没有辐射风险，设备价格低以及能够实时获取图像。很多超声应用的第一步通常是对感兴趣组织和结构的检测和定位。然而，超声图像存在一些特有的伪影，比如高噪声，低信噪比和灰度不均，这些伪影使得检测任务变得困难。此外，感兴趣区域之间的低对比度也使得这一任务变得更加复杂。在这篇论文里，我们深入研究这些图像伪影并提出新的方法来促进临床中的超声应用。 / 首先，我们提出一个多尺度的框架来进行超声图像的分割，这个框架是基于各向异性去噪扩散和测地主动轮廓线的。各向异性去噪扩散是对边缘敏感且专门用于斑点噪声图像的扩散过程，这里它被用来去除超声图像的斑点噪声，我们对每幅输入图像构造一个多尺度的表示方法，随着尺度的增加，噪声被逐渐地消除。之后，多尺度测地主动轮廓线从粗到细渐进地应用到这些尺度来提取物体的边界线。为了避免在低对比度区域出现边界泄漏的情况，我们把不同尺度之间的边界形状相似性结合到传统的测地主动轮廓线模型里作为一个外部约束来指导轮廓线的演化。在合成和临床图像的实验结果证明了我们的方法的优越性。 / 其次，我们提出一个基于相位的方法来检查和测量超声图像里的胎儿腹部轮廓线。我们定义了一个基于局部相位的度量来检测胎儿腹部的边界线，这个度量称为多尺度特征非对称性，它与图像的亮度无关，并且能为图像里特征的重要程度提供一个绝对的测量。为了估计与腹部轮廓线相吻合的椭圆，我们使用一个迭代随机霍夫变换来排除内腹部边界线的影响，从而使得估计的椭圆逐渐收敛到外边界线。在临床超声图像里进行腹部周长测量的实验结果验证了我们的方法与手工的方法有很高的一致性，这也表明我们的方法可以作为一个可靠的工具来进行产科的护理和诊断。 / Ultrasound imaging is one of the most widely used diagnostic and therapeutic tools for a variety of clinical applications. Compared with other imaging modalities, such as computed tomography and magnetic resonance imaging, ultrasonography has a lot of advantages: free of radiation risk, low cost of acquisition and images are available in real-time. The first step in many ultrasonic applications is usually the detection and localization of interested tissues and structures. However, there are a number of characteristic artifacts in ultrasound images that make the task difficult such as high speckle noise, low signal-to-noise ratio and intensity inhomogeneity. Besides, the low contrast between regions of interest further complicates the processing. In this thesis, we deeply investigate these image artifacts and propose new techniques to facilitate ultrasonic applications in clinic. / First, we propose a multiscale framework for ultrasound image segmentation based on speckle reducing anisotropic diffusion(SRAD) and geodesic active contours (GAC). SRAD is an edge-sensitive diffusion tailored for speckled images, and it is adopted here to reduce speckle noise by constructing a multiscale representation for each input image, where the noise is gradually removed as the scale increases. Multiscale geodesic active contours are then applied along the scales in a coarse-to-fine manner to capture the object boundaries progressively. To avoid boundary leakages in low contrast regions, traditional GAC model is modified by incorporating the boundary shape similarity between different scales as an external constraint to guide the contour evolution. Experimental results in both synthetic and clinical images demonstrate the superiority of the proposed approach. / Second, we propose a phase-based approach for fetal abdominal contour detection and measurement in ultrasound images.We define a local phase-based measure, called multiscale feature asymmetry (MSFA), from the monogenic signal to detect the boundaries of fetal abdomen. The MSFA measure is intensity invariant and provides an absolute measurement for the significance of features in the image. In order to estimate the ellipse that fits to the abdominal contour, we employ an iterative randomized Hough transform to exclude the interferences of the inner boundaries of the abdomen, after which the estimated ellipse gradually converges to the outer boundaries. Experimental results in clinical ultrasound images validate the high agreement between our approach and manual approach in the measurement of abdominal circumference, indicating that the proposed approach can be used as a reliable tool for obstetric care and diagnosis. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Wang, Weiming . / Thesis (Ph.D.) Chinese University of Hong Kong, 2014. / Includes bibliographical references (leaves 68-84). / Abstracts also in Chinese. / Wang, Weiming .