Transmission/Reflection Dual-mode Ultrasonic Tomography using Weighted Least Square-Lagrange Joint Reconstruction

Industrial Ultrasonic Tomography (UT) possesses unique advantages in multiphase medium imaging and has received broad attention. In this work, a novel transmission/reflection dual-mode image reconstruction algorithm based on information fusion is proposed. The transmissive attenuation and reflective time-delay information are both integrated into an improved Lagrange framework with the weighted least square transformation of objective function, which is then solved by a pair of coupled preconditioned gradient approaches. Experiment results show that the proposed algorithm performs better than existing image fusion strategies in terms of accuracy (average relative error 0.456, average correlation coefficient 0.870) and robustness (average standard derivation of relative error and correlation coefficient 0.056 and 0.041). Accordingly, the dual-mode UT approach is proved feasible to provide more accurate image of biphasic medium distribution

Image Reconstruction of the Speed of Sound and Initial Pressure Distributions in Ultrasound Computed Tomography and Photoacoustic Computed Tomography

Ultrasound computed tomography (USCT) and photoacoustic computed tomography (PACT) are two emerging imaging modalities that have a wide range of potential applications from pre-clinical small animal imaging to cancer screening in human subjects. USCT is typically employed to measure acoustic contrasts, including the speed of sound (SOS) distribution, while PACT typically measures optical contrasts or some related quantity such as the initial pressure distribution. Their complementary contrasts and similar implementations make USCT and PACT a natural fit for a hybrid imaging system. Still, much work remains to realize this promise. First, USCT image reconstruction methods based on the acoustic wave equation, known as waveform inversion methods, are computationally burdensome, limiting their widespread use. Instead, image reconstruction methods based on geometric acoustics are often employed. These methods do not model higher-order diffraction effects and consequentially have poor resolution. In this dissertation, use of a novel stochastic optimization method, which overcomes much of the computational burden of waveform inversion, is proposed. Second, most traditional PACT image reconstruction algorithms assume a constant SOS distribution. For many biological applications, this is a poor assumption that can result in reduced resolution, reduced contrast, and an increase in the number of imaging artifacts. More recent image reconstruction algorithms can compensate for a known heterogeneous SOS distribution; however, in practice, the SOS distribution is not known. Further, in general, the joint reconstruction (JR) of the SOS and initial pressure distributions from PACT measurements is unstable. Two methods are proposed to overcome this problem. In the first, a parameterized JR method is employed. Under this approach, the SOS distribution is assumed to have a known low-dimensional representation. By constraining the form of the SOS distribution, the JR problem can be made more stable. In the second method, few-view USCT measurements are added to the PACT data, and the initial pressure and SOS distributions are jointly estimated from the combined measurements. This approach effectively exploits acoustic information present in the PACT data, allowing both the initial pressure and SOS distributions to be more accurately reconstructed

Real-time quantitative sonoelastography in an ultrasound research system

Quantitative Sono-Elastographie ist eine neue Technologie für die Ultraschall Bildgebung, die Radiologen maligne Tumoren ohne Risiko der strahlungsinduzierten Krebs (d.h. Mammographie) zu erfassen können. Aufgrund gefunden Rechenkomplexität in der aktuellen Algorithmen, Implementierung von Echtzeit-Anwendungen, die Prüfungsverfahren profitieren wurde jedoch noch nicht berichtet. Zusätzlich, aktuelle Schätzer für die Darstellung eine Elastizität Bilder vorhanden Artefakte der hohen Schätzung Varianz, die die Techniker in die Gegenwart steifer Massen irreführen könnten und zwar, falsch-positive Diagnose zu erzeugen. In dieser Arbeit wird eine GPU-basierte Elastographie-System entwickelt und an einem Forschungsultraschallgeräten implementiert. Quantitative Elastizität in Echtzeit bei 2 FPS mit einer Verbesserung Rechenzeitfaktor aus 26 wird gezeigt. Validierung der Systemgenauigkeit Anzeige wurde, auf Gelatinebasis Gewebe Phantome durchgeführt., waren niedrige Vorspannung der Elastizitätswerte berichtet wurde (4,7 %) bei geringe Anregungsfrequenzen nachahmt. Ausserdem wird eine neue Elastizität Schätzer auf quantitative Sono-Elastographie basiert eingeführt. Ein lineares Problem wurde entlang der seitlichen Abmessung modelliert und eine Regularisierung Methode wurde implementieren. Elastizität Bilder mit niedriger Vorspannung wurde darstellen (1,48 %) sowie seine Leistung in einer Brust kalibrierte Phantom mit verbesserter CNR (47,3 dB) im Vergleich mit anderen Schätzer ausgewertet sowie die Verringerung Seiten Artefakte bereits erwähnt in der Literatur (PD: 22,7 dB, 1DH 28,7 dB) gefunden. Diese zwei Beitrag profitieren, die Umsetzung und Entwicklung weiterer Elastographie Techniken, die eine verbesserte Qualität der Elastizität Bilder liefern könnten und somit eine verbesserte Genauigkeit der Diagnose.Quantitative sonoelastography is an alternative technology for ultrasound imaging that helps radiologist to diagnose malignant tumors with no risk of radiation-induced cancer (i.e. mammography). However, due to the high computational complexity found in the current algorithms, implementation of real-time systems that could benefit examination procedures has not been yet reported. Additionally, elasticity maps depicted from current estimators feature artifacts of high estimation variance that could mislead the technician into the presence of stiffer masses, generating false positive diagnosis. In this thesis, a GPU-based elastography system was designed and implemented on a research ultrasound equipment, displaying quantitative elasticity in real-time at 2 FPS with an improvement computational time factor of 26. Validation of the system accuracy was conducted on gelatin-based tissue mimicking phantoms, where low bias of elasticity values were reported (4.7%) at low excitation frequencies. Additionally, a new elasticity estimator based on quantitative sonoelastography was developed. A linear problem was modeled from the acquired sonolastography data along the lateral dimension and a regularization method was implemented. The resulting elasticity images presented low bias (1.48%), enhanced CNR and reduced lateral artifacts when evaluating the algorithm’s performance in a breast calibrated phantom and comparing it with other estimators found in the literature. These two contribution benefit the implementation and development of further elastography techniques that could provide enhanced quality of elasticity images and thus, improved accuracy of diagnosis.Tesi

Three-Dimensional Photoacoustic Computed Tomography: Imaging Models and Reconstruction Algorithms

Photoacoustic computed tomography: PACT), also known as optoacoustic tomography, is a rapidly emerging imaging modality that holds great promise for a wide range of biomedical imaging applications. Much effort has been devoted to the investigation of imaging physics and the optimization of experimental designs. Meanwhile, a variety of image reconstruction algorithms have been developed for the purpose of computed tomography. Most of these algorithms assume full knowledge of the acoustic pressure function on a measurement surface that either encloses the object or extends to infinity, which poses many difficulties for practical applications. To overcome these limitations, iterative image reconstruction algorithms have been actively investigated. However, little work has been conducted on imaging models that incorporate the characteristics of data acquisition systems. Moreover, when applying to experimental data, most studies simplify the inherent three-dimensional wave propagation as two-dimensional imaging models by introducing heuristic assumptions on the transducer responses and/or the object structures. One important reason is because three-dimensional image reconstruction is computationally burdensome. The inaccurate imaging models severely limit the performance of iterative image reconstruction algorithms in practice. In the dissertation, we propose a framework to construct imaging models that incorporate the characteristics of ultrasonic transducers. Based on the imaging models, we systematically investigate various iterative image reconstruction algorithms, including advanced algorithms that employ total variation-norm regularization. In order to accelerate three-dimensional image reconstruction, we develop parallel implementations on graphic processing units. In addition, we derive a fast Fourier-transform based analytical image reconstruction formula. By use of iterative image reconstruction algorithms based on the proposed imaging models, PACT imaging scanners can have a compact size while maintaining high spatial resolution. The research demonstrates, for the first time, the feasibility and advantages of iterative image reconstruction algorithms in three-dimensional PACT

System Characterizations and Optimized Reconstruction Methods for Novel X-ray Imaging

In the past decade there have been many new emerging X-ray based imaging technologies developed for different diagnostic purposes or imaging tasks. However, there exist one or more specific problems that prevent them from being effectively or efficiently employed. In this dissertation, four different novel X-ray based imaging technologies are discussed, including propagation-based phase-contrast (PB-XPC) tomosynthesis, differential X-ray phase-contrast tomography (D-XPCT), projection-based dual-energy computed radiography (DECR), and tetrahedron beam computed tomography (TBCT). System characteristics are analyzed or optimized reconstruction methods are proposed for these imaging modalities. In the first part, we investigated the unique properties of propagation-based phase-contrast imaging technique when combined with the X-ray tomosynthesis. Fourier slice theorem implies that the high frequency components collected in the tomosynthesis data can be more reliably reconstructed. It is observed that the fringes or boundary enhancement introduced by the phase-contrast effects can serve as an accurate indicator of the true depth position in the tomosynthesis in-plane image. In the second part, we derived a sub-space framework to reconstruct images from few-view D-XPCT data set. By introducing a proper mask, the high frequency contents of the image can be theoretically preserved in a certain region of interest. A two-step reconstruction strategy is developed to mitigate the risk of subtle structures being oversmoothed when the commonly used total-variation regularization is employed in the conventional iterative framework. In the thirt part, we proposed a practical method to improve the quantitative accuracy of the projection-based dual-energy material decomposition. It is demonstrated that applying a total-projection-length constraint along with the dual-energy measurements can achieve a stabilized numerical solution of the decomposition problem, thus overcoming the disadvantages of the conventional approach that was extremely sensitive to noise corruption. In the final part, we described the modified filtered backprojection and iterative image reconstruction algorithms specifically developed for TBCT. Special parallelization strategies are designed to facilitate the use of GPU computing, showing demonstrated capability of producing high quality reconstructed volumetric images with a super fast computational speed. For all the investigations mentioned above, both simulation and experimental studies have been conducted to demonstrate the feasibility and effectiveness of the proposed methodologies

Characterization of carotid artery plaques using noninvasive vascular ultrasound elastography

L'athérosclérose est une maladie vasculaire complexe qui affecte la paroi des artères (par l'épaississement) et les lumières (par la formation de plaques). La rupture d'une plaque de l'artère carotide peut également provoquer un accident vasculaire cérébral ischémique et des complications. Bien que plusieurs modalités d'imagerie médicale soient actuellement utilisées pour évaluer la stabilité d'une plaque, elles présentent des limitations telles que l'irradiation, les propriétés invasives, une faible disponibilité clinique et un coût élevé. L'échographie est une méthode d'imagerie sûre qui permet une analyse en temps réel pour l'évaluation des tissus biologiques. Il est intéressant et prometteur d’appliquer une échographie vasculaire pour le dépistage et le diagnostic précoces des plaques d’artère carotide. Cependant, les ultrasons vasculaires actuels identifient uniquement la morphologie d'une plaque en termes de luminosité d'écho ou l’impact de cette plaque sur les caractéristiques de l’écoulement sanguin, ce qui peut ne pas être suffisant pour diagnostiquer l’importance de la plaque. La technique d’élastographie vasculaire non-intrusive (« noninvasive vascular elastography (NIVE) ») a montré le potentiel de détermination de la stabilité d'une plaque. NIVE peut déterminer le champ de déformation de la paroi vasculaire en mouvement d’une artère carotide provoqué par la pulsation cardiaque naturelle. En raison des différences de module de Young entre les différents tissus des vaisseaux, différents composants d’une plaque devraient présenter différentes déformations, caractérisant ainsi la stabilité de la plaque. Actuellement, les performances et l’efficacité numérique sous-optimales limitent l’acceptation clinique de NIVE en tant que méthode rapide et efficace pour le diagnostic précoce des plaques vulnérables. Par conséquent, il est nécessaire de développer NIVE en tant qu’outil d’imagerie non invasif, rapide et économique afin de mieux caractériser la vulnérabilité liée à la plaque. La procédure à suivre pour effectuer l’analyse NIVE consiste en des étapes de formation et de post-traitement d’images. Cette thèse vise à améliorer systématiquement la précision de ces deux aspects de NIVE afin de faciliter la prédiction de la vulnérabilité de la plaque carotidienne. Le premier effort de cette thèse a été dédié à la formation d'images (Chapitre 5). L'imagerie par oscillations transversales a été introduite dans NIVE. Les performances de l’imagerie par oscillations transversales couplées à deux estimateurs de contrainte fondés sur un modèle de déformation fine, soit l’ « affine phase-based estimator (APBE) » et le « Lagrangian speckle model estimator (LSME) », ont été évaluées. Pour toutes les études de simulation et in vitro de ce travail, le LSME sans imagerie par oscillation transversale a surperformé par rapport à l'APBE avec imagerie par oscillations transversales. Néanmoins, des estimations de contrainte principales comparables ou meilleures pourraient être obtenues avec le LSME en utilisant une imagerie par oscillations transversales dans le cas de structures tissulaires complexes et hétérogènes. Lors de l'acquisition de signaux ultrasonores pour la formation d'images, des mouvements hors du plan perpendiculaire au plan de balayage bidimensionnel (2-D) existent. Le deuxième objectif de cette thèse était d'évaluer l'influence des mouvements hors plan sur les performances du NIVE 2-D (Chapitre 6). À cette fin, nous avons conçu un dispositif expérimental in vitro permettant de simuler des mouvements hors plan de 1 mm, 2 mm et 3 mm. Les résultats in vitro ont montré plus d'artefacts d'estimation de contrainte pour le LSME avec des amplitudes croissantes de mouvements hors du plan principal de l’image. Malgré tout, nous avons néanmoins obtenu des estimations de déformations robustes avec un mouvement hors plan de 2.0 mm (coefficients de corrélation supérieurs à 0.85). Pour un jeu de données cliniques de 18 participants présentant une sténose de l'artère carotide, nous avons proposé d'utiliser deux jeux de données d'analyses sur la même plaque carotidienne, soit des images transversales et longitudinales, afin de déduire les mouvements hors plan (qui se sont avérés de 0.25 mm à 1.04 mm). Les résultats cliniques ont montré que les estimations de déformations restaient reproductibles pour toutes les amplitudes de mouvement, puisque les coefficients de corrélation inter-images étaient supérieurs à 0.70 et que les corrélations croisées normalisées entre les images radiofréquences étaient supérieures à 0.93, ce qui a permis de démontrer une plus grande confiance lors de l'analyse de jeu de données cliniques de plaques carotides à l'aide du LSME. Enfin, en ce qui concerne le post-traitement des images, les algorithmes NIVE doivent estimer les déformations des parois des vaisseaux à partir d’images reconstituées dans le but d’identifier les tissus mous et durs. Ainsi, le dernier objectif de cette thèse était de développer un algorithme d'estimation de contrainte avec une résolution de la taille d’un pixel ainsi qu'une efficacité de calcul élevée pour l'amélioration de la précision de NIVE (Chapitre 7). Nous avons proposé un estimateur de déformation de modèle fragmenté (SMSE) avec lequel le champ de déformation dense est paramétré avec des descriptions de transformées en cosinus discret, générant ainsi des composantes de déformations affines (déformations axiales et latérales et en cisaillement) sans opération mathématique de dérivées. En comparant avec le LSME, le SMSE a réduit les erreurs d'estimation lors des tests de simulations, ainsi que pour les mesures in vitro et in vivo. De plus, la faible mise en oeuvre de la méthode SMSE réduit de 4 à 25 fois le temps de traitement par rapport à la méthode LSME pour les simulations, les études in vitro et in vivo, ce qui pourrait permettre une implémentation possible de NIVE en temps réel.Atherosclerosis is a complex vascular disease that affects artery walls (by thickening) and lumens (by plaque formation). The rupture of a carotid artery plaque may also induce ischemic stroke and complications. Despite the use of several medical imaging modalities to evaluate the stability of a plaque, they present limitations such as irradiation, invasive property, low clinical availability and high cost. Ultrasound is a safe imaging method with a real time capability for assessment of biological tissues. It is clinically used for early screening and diagnosis of carotid artery plaques. However, current vascular ultrasound technologies only identify the morphology of a plaque in terms of echo brightness or the impact of the vessel narrowing on flow properties, which may not be sufficient for optimum diagnosis. Noninvasive vascular elastography (NIVE) has been shown of interest for determining the stability of a plaque. Specifically, NIVE can determine the strain field of the moving vessel wall of a carotid artery caused by the natural cardiac pulsation. Due to Young’s modulus differences among different vessel tissues, different components of a plaque can be detected as they present different strains thereby potentially helping in characterizing the plaque stability. Currently, sub-optimum performance and computational efficiency limit the clinical acceptance of NIVE as a fast and efficient method for the early diagnosis of vulnerable plaques. Therefore, there is a need to further develop NIVE as a non-invasive, fast and low computational cost imaging tool to better characterize the plaque vulnerability. The procedure to perform NIVE analysis consists in image formation and image post-processing steps. This thesis aimed to systematically improve the accuracy of these two aspects of NIVE to facilitate predicting carotid plaque vulnerability. The first effort of this thesis has been targeted on improving the image formation (Chapter 5). Transverse oscillation beamforming was introduced into NIVE. The performance of transverse oscillation imaging coupled with two model-based strain estimators, the affine phase-based estimator (APBE) and the Lagrangian speckle model estimator (LSME), were evaluated. For all simulations and in vitro studies, the LSME without transverse oscillation imaging outperformed the APBE with transverse oscillation imaging. Nonetheless, comparable or better principal strain estimates could be obtained with the LSME using transverse oscillation imaging in the case of complex and heterogeneous tissue structures. During the acquisition of ultrasound signals for image formation, out-of-plane motions which are perpendicular to the two-dimensional (2-D) scan plane are existing. The second objective of this thesis was to evaluate the influence of out-of-plane motions on the performance of 2-D NIVE (Chapter 6). For this purpose, we designed an in vitro experimental setup to simulate out-of-plane motions of 1 mm, 2 mm and 3 mm. The in vitro results showed more strain estimation artifacts for the LSME with increasing magnitudes of out-of-plane motions. Even so, robust strain estimations were nevertheless obtained with 2.0 mm out-of-plane motion (correlation coefficients higher than 0.85). For a clinical dataset of 18 participants with carotid artery stenosis, we proposed to use two datasets of scans on the same carotid plaque, one cross-sectional and the other in a longitudinal view, to deduce the out-of-plane motions (estimated to be ranging from 0.25 mm to 1.04 mm). Clinical results showed that strain estimations remained reproducible for all motion magnitudes since inter-frame correlation coefficients were higher than 0.70, and normalized cross-correlations between radiofrequency images were above 0.93, which indicated that confident motion estimations can be obtained when analyzing clinical dataset of carotid plaques using the LSME. Finally, regarding the image post-processing component of NIVE algorithms to estimate strains of vessel walls from reconstructed images with the objective of identifying soft and hard tissues, we developed a strain estimation method with a pixel-wise resolution as well as a high computation efficiency for improving NIVE (Chapter 7). We proposed a sparse model strain estimator (SMSE) for which the dense strain field is parameterized with Discrete Cosine Transform descriptions, thereby deriving affine strain components (axial and lateral strains and shears) without mathematical derivative operations. Compared with the LSME, the SMSE reduced estimation errors in simulations, in vitro and in vivo tests. Moreover, the sparse implementation of the SMSE reduced the processing time by a factor of 4 to 25 compared with the LSME based on simulations, in vitro and in vivo results, which is suggesting a possible implementation of NIVE in real time