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Quantitative techniques for permanent breast seed implant brachytherapyMorton, Daniel R. 04 October 2017 (has links)
Permanent breast seed implant brachytherapy (PBSI) is a recently developed form of treatment for early-stage breast cancer which can be completed in a single day procedure. Due to the reduced treatment burden, PBSI has the potential to benefit many women. However the technique has not been widely implemented, potentially related to the lack of a standardized, reproducible procedure and a high level of operator dependence. Challenges relating to target visualization uncertainties and the reliance on free-hand 2D ultrasound (US) guidance potentially inhibit adoption of the technique. This work aims to evaluate the current PBSI procedure to identify uncertainties and potential sources of errors in the current technique and develop methods to ameliorate these issues to potentially increase treatment accuracy, standardize the procedure, and reduce user-dependence.
A comprehensive assessment of the current PBSI procedure was performed to identify any trends or systematic errors in the placement of seeds and establish the effects of seed placement accuracy on the treatment. Baseline seed placement accuracy, assessed in a 20 patient cohort was observed to be 9(5) mm. Random displacements of seeds from their planned position contributed significantly to the overall accuracy. No trends or systematic errors were observed across the aggregate population, however intra-patient systematic offsets were observed. The potential effects of visualization of the post-lumpectomy cavity (seroma) on treatment delivery was investigated using spatially registered CT and 3DUS images. Planning the treatment on CT, as is standard practice, resulted in less than optimal coverage to target volumes defined on US in the majority of cases. The effects of intra-operative adjustments relating to the visualization differences on the two modalities was assessed by shifting the CT-based treatment plan to centre on the US-defined seroma. Such shifts were shown to potentially contribute to the systematic displacements observed in PBSI delivery, and also had significant dosimetric effects on the planned target volumes.
The impact of seroma visualization on PBSI implant accuracy was further assessed through the evaluation of CT and 3DUS images acquired for PBSI patients. Correlations were observed between the seed placement accuracy and the inter-user variability of seroma definition on CT (r = 0.74, p = 0.01) and the volume difference of the seroma on the two modalities (r = 0.65, p = 0.04), indicating that discrepancies in target delineation can impact treatment accuracy. The systematic displacements of the implants were observed to be correlated with the visualization metrics, however random displacements were independent of seroma delineation.
Deviations in needle positioning during insertion may not be realized until the implant is complete, thus contributing to the random inaccuracies in seed placement. A purpose built 3DUS scanning system was investigated for its use in guiding needle insertion. Registration of the treatment template with the imaging system was validated to provide accurate target localization for needle insertion. Adjustments and re-insertion of needles under 3DUS guidance provided significant improvements to the needle positioning accuracy. A simulated implant with the guidance system indicated that overall treatment accuracy may be improved through the clinical implementation of such a system.
Efforts to improve seroma definition during treatment planning and image guidance during the delivery can significantly increase seed placement accuracy and reduce the need for subjective intra-operative adjustments to the setup and needle positioning. Standardization of such advanced imaging techniques can greatly benefit the PBSI procedure by reducing user dependence and help to promote implementation. / Graduate / 2018-09-22
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Engineering a 3D ultrasound system for image-guided vascular modellingHammer, Steven James January 2009 (has links)
Atherosclerosis is often diagnosed using an ultrasound (US) examination in the carotid and femoral arteries and the abdominal aorta. A decision to operate requires two measures of disease severity: the degree of stenosis measured using B-mode US; and the blood flow patterns in the artery measured using spectral Doppler US. However other biomechanical factors such as wall shear stress (WSS) and areas of flow recirculation are also important in disease development and rupture. These are estimated using an image-guided modelling approach, where a three-dimensional computational mesh of the artery is simulated. To generate a patient-specific arterial 3D computational mesh, a 3D ultrasound (3DUS) system was developed. This system uses a standard clinical US scanner with an optical position sensor to measure the position of the transducer; a video capture card to record video images from the scanner; and a PC running Stradwin software to reconstruct 3DUS data. The system was characterised using an industry-standard set of calibration phantoms, giving a reconstruction accuracy of ± 0.17 mm with a 12MHz linear array transducer. Artery movements from pulsatile flow were reduced using a retrospective gating technique. The effect of pressure applied to the transducer moving and deforming the artery was reduced using an image-based rigid registration technique. The artery lumen found on each 3DUS image was segmented using a semi-automatic segmentation technique known as ShIRT (the Sheffield Image Registration Toolkit). Arterial scans from healthy volunteers and patients with diagnosed arterial disease were segmented using the technique. The accuracy of the semi-automatic technique was assessed by comparing it to manual segmentation of each artery using a set of segmentation metrics. The mean accuracy of the semi-automatic technique ranged from 85% to 99% and depended on the quality of the images and the complexity of the shape of the lumen. Patient-specific 3D computational artery meshes were created using ShIRT. An idealised mesh was created using key features of the segmented 3DUS scan. This was registered and deformed to the rest of the segmented dataset, producing a mesh that represents the shape of the artery. Meshes created using ShIRT were compared to meshes created using the Rhino solid modelling package. ShIRT produced smoother meshes; Rhino reproduced the shape of arterial disease more accurately. The use of 3DUS with image-guided modelling has the potential to be an effective tool in the diagnosis of atherosclerosis. Simulations using these data reflect in vivo studies of wall shear stress and recirculation in diseased arteries and are comparable with results in the literature created using MRI and other 3DUS systems.
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Real-time tracking of deformable targets in 3D ultrasound sequences / Suivi temps-réel de cibles dans des séquences de volumes échographiquesRoyer, Lucas 06 December 2016 (has links)
De nos jours, les traitements mini-invasifs, tels que l'ablation par radiofréquence, sont de plus en plus utilisés car ils permettent d'éliminer localement les tumeurs à partir de l'insertion d'une aiguille. Cependant, le succès de ces procédures dépend de la précision du positionnement de l'aiguille par rapport aux structures anatomiques. Afin de garantir un placement correct, l'imagerie échographique est souvent utilisée car elle a l'avantage d'être temps-réelle, bas coût, et non-invasive. En revanche, celle modalité peut compliquer la visualisation de certaines structures en raison de sa qualité et de son champ de vue limité. En outre, la précision des interventions peut aussi être perturbée par les déplacements de tissus liés aux mouvements physiologiques du patient et à la manipulation d'instruments médicaux. Afin d'aider le chirurgien à mieux cibler certaines structures anatomiques, de nombreuses équipes de recherche ont proposé des travaux permettant d'estimer la position de régions d'intérêts dans l'imagerie échographique. Cette thèse propose plusieurs contributions permettant de suivre en temps réel des structures déformables dans des séquences d'échographie 3D. Une première contribution repose sur l'utilisation conjointe de l'information visuelle dense et d'une méthode de simulation physique. Dans cette thèse, nous avons aussi proposé un nouveau critère de similarité spécifique à l'imagerie échographique basé sur une étape de détection d'ombres. Enfin, la dernière contribution est liée à une stratégie de suivi hybride permettant d'améliorer la qualité des images. A partir de ces contributions, nous proposons une méthode de suivi robuste au bruit de type« speckle », aux ombres et aux changements d'intensité perturbant l'imagerie échographique. Les performances des différentes contributions sont évaluées à partir de données simulées et de données acquises sur maquettes et sur volontaires humains. Ces résultats montrent que notre méthode est robuste à différents artefacts de l'imagerie échographique. En outre, nous démontrons la performance de notre approche par rapport à différentes méthodes de l'état de l'art sur des bases de données publiques fournies par les challenges MICCAI CLUST'14 et CLUST'15. Dans cette thèse, nous proposons également une application permettant de combiner l'imagerie échographique à l'imagerie par résonance magnétique (IRM). Cette méthode permet d'observer des structures anatomiques non-visibles dans l'imagerie échographique durant l'intervention. Elle est basée sur la combinaison d'une méthode de suivi et d'un recalage multi-modal obtenu à partir d'un système de localisation externe. Cette application a été évaluée sur un volontaire sain à partir d'une plateforme liée au centre Hospitalier Universitaire de Rennes. / Nowadays, mini-invasive treatments, such as radio-frequency ablation, are increasingly being used because they allow eliminating tumors locally from needle insertion. However, the success of these therapies depends on the accurate positioning of the needle with respect to anatomical structures. To ensure correct placement, ultrasound (US) imaging is often used since this system has the advantage to be real-time, low-cost, and non-invasive. However, during the intervention, US imaging can complicate the visualization of targeted structures due to its poor quality and its limited field of view. Furthermore, the accuracy of these interventions may also be perturbed by both physiological movements and medical tools displacements that introduce motions of anatomical structures. To help the surgeon to better target malignant tissues, many research teams have proposed different method in order to estimate the position of regions of interest in ultrasound imaging. This thesis provides several contributions that allow tracking deformable structures in 3D ultrasound sequences. We first present a method that allows providing robust estimation of target positions by combining an intensity-based approach and mechanical model simulation. In this thesis, we also propose novel ultrasound-specific similarity criterion based on prior step that aims at detecting shadows. The last contribution is related to a hybrid tracking strategy that allows improving quality of ultrasound images. From these contributions, we propose a tracking method that has the advantage to be invariant to speckle noise, shadowing and intensity changes that can occur in US imaging. The performance and limitations of the proposed contributions are evaluated through simulated data, phantom data, and real-data obtained from different volunteers. Simulation and phantom results show that our method is robust to several artefacts of US imaging such as shadows and speckle decorrelation. Furthermore, we demonstrate that our approach outperforms state-of-the-art methods on the 3D public databases provided by MICCAI CLUST'14 and CLUST'15 challenges. In this thesis, we also propose an application that combines ultrasound imaging to Magnetic Resonance lmaging (MRI). This method allows observing anatomical structures that are not visible in US imaging during the intervention. It is based on the combination between US tracking method and multi modal registration obtained from external localization system. This application was evaluated on a volunteer thanks to an MRJ imaging platform locate at the University Hospital of Rennes.
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Real-time Control of Radiofrequency Thermal Ablation using Three-dimensional Ultrasound Echo Decorrelation Imaging FeedbackGrimm, Peter January 2022 (has links)
No description available.
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Semi-Automated Segmentation of 3D Medical Ultrasound ImagesQuartararo, John David 05 February 2009 (has links)
A level set-based segmentation procedure has been implemented to identify target object boundaries from 3D medical ultrasound images. Several test images (simulated, scanned phantoms, clinical) were subjected to various preprocessing methods and segmented. Two metrics of segmentation accuracy were used to compare the segmentation results to ground truth models and determine which preprocessing methods resulted in the best segmentations. It was found that by using an anisotropic diffusion filtering method to reduce speckle type noise with a 3D active contour segmentation routine using the level set method resulted in semi-automated segmentation on par with medical doctors hand-outlining the same images.
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The Ultrasound Brain Helmet: Simultaneous Multi-transducer 3D Transcranial Ultrasound ImagingLindsey, Brooks January 2012 (has links)
<p>In this work, I examine the problem of rapid imaging of stroke and present ultrasound-based approaches for addressing it. Specifically, this dissertation discusses aberration and attenuation due to the skull as sources of image degradation and presents a prototype system for simultaneous 3D bilateral imaging via both temporal acoustic windows. This system uses custom sparse array transducers built on flexible multilayer circuits that can be positioned for simultaneous imaging via both temporal acoustic windows, allowing for registration and fusion of multiple real-time 3D scans of cerebral vasculature. I examine hardware considerations for new matrix arrays--transducer design and interconnects--in this application. Specifically, it is proposed that signal-to-noise ratio (SNR) may be increased by reducing the length of probe cables. This claim is evaluated as part of the presented system through simulation, experimental data, and in vivo imaging. Ultimately, gains in SNR of 7 dB are realized by replacing a standard probe cable with a much shorter flex interconnect; higher gains may be possible using ribbon-based probe cables. In vivo images are presented depicting cerebral arteries with and without the use of microbubble contrast agent that have been registered and fused using a search algorithm which maximizes normalized cross-correlation. </p><p>The scanning geometry of a brain helmet-type system is also utilized to allow each matrix array to serve as a correction source for the opposing array. Aberration is estimated using cross-correlation of RF channel signals followed by least mean squares solution of the resulting overdetermined system. Delay maps are updated and real-time 3D scanning resumes. A first attempt is made at using multiple arrival time maps to correct multiple unique aberrators within a single transcranial imaging volume, i.e. several isoplanatic patches. This adaptive imaging technique, which uses steered unfocused waves transmitted by the opposing or "beacon" array, updates the transmit and receive delays of 5 isoplanatic patches within a 64°×64° volume. In phantom experiments, color flow voxels above a common threshold have increased by an average of 92% while color flow variance decreased by an average of 10%. This approach has been applied to both temporal acoustic windows of two human subjects, yielding increases in echo brightness in 5 isoplanatic patches with a mean value of 24.3 ± 9.1%, suggesting such a technique may be beneficial in the future for improving image quality in non-invasive 3D color flow imaging of cerebrovascular disease including stroke.</p><p>Acoustic window failure and the possibility of overcoming it using a low frequency, large aperture array are also examined. In performing transcranial ultrasound examinations, 8-29% of patients in a general population may present with window failure, in which it is not possible to acquire clinically useful sonographic information through the temporal acoustic window. The incidence of window failure is higher in the elderly and in populations of African descent, making window failure an important concern for stroke imaging through the intact skull. To this end, I describe the technical considerations, design, and fabrication of low-frequency (1.2 MHz), large aperture (25.3 mm) sparse matrix array transducers for 3D imaging in the event of window failure. These transducers are integrated into the existing system for real-time 3D bilateral transcranial imaging and color flow imaging capabilities at 1.2 MHz are directly compared with arrays operating at 1.8 MHz in a flow phantom with approximately 47 dB/cm0.8/MHz0.8 attenuators. In vivo contrast-enhanced imaging allowed visualization of the arteries of the Circle of Willis in 5 of 5 subjects and 8 of 10 sides of the head despite probe placement outside of the acoustic window. Results suggest that the decrease from approximately 2 to 1 MHz for 3D transcranial ultrasound may be sufficient to allow acquisition of useful images either in individuals with poor windows or outside of the temporal acoustic window by untrained operators in the field.</p> / Dissertation
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Reconstruction 3D du segment antérieur oculaire par échographie haute fréquence / Reconstruction 3D of the anterior eye segment by echography high frequencyKohandani Tafreshi, Marzieh 17 February 2014 (has links)
Une des applications de l’échographie médicale est celle de l’ophtalmologie qui pose de nombreux problèmes spécifiques liés en partie à la faible dimension de l’oeil et à la précision importante que requièrent les mesures intraoculaires. En effet, avec le développement de la chirurgie réfractive qui regroupe ensemble des techniques capables de corriger les erreurs de réfraction et l’avènement des implants intraoculaires, le chirurgien ophtalmologiste est amené à surveiller la tolérance et les effets secondaires de ces implants sur les structures du segment antérieur. L’échographie à haute fréquence apporte la résolution suffisante pour cette tâche. Cependant, le développement de l’échographie 3D permet une extension des applications ophtalmologiques notamment pour le dimensionnement des implants en préopératoire. La modélisation 3D du segment antérieur permet d’étudier le comportement des implants et surtout de dessiner à terme un implant « sur mesure » pour le patient. C’est dans ce contexte que nous présentons une méthode originale de segmentation et de reconstruction 3D du segment antérieur par échographique haute fréquence en utilisant l’ajustement de modèles 3D. Nous utilisons un système échographique 3D de type main-libre, composé d’une sonde échographique haute fréquence, et d’un module de localisation actif comprenant une caméra et des marqueurs infrarouges. Ce système échographique 3D nous permet d’obtenir des images avec des informations de positionnement dans l’espace tridimensionnel associées. Nous avons ainsi pu mettre en place toute une chaîne d’acquisitions et de traitements des images échographiques. Nous créons, à partir d’images échographiques du segment antérieur oculaire, des modèles de référence 3D réalistes. Nous proposons ainsi une méthode d’ajustement de modèles 3D de référence sur des données 3D échographiques via l’utilisation de l’algorithme de recalage ICP. Nous avons également sélectionné et adapté différentes méthodes pour l’évaluation de l’approche de reconstruction proposée. Ces méthodes permettent de mettre en valeur la précision de ces reconstructions. / Ophthalmology is one of the clinical application fields of ultrasound imaging, for which numerous specific issues arise, related in part to the eye’s small anatomical dimensions combined with the high level of accuracy requirements associated with intraocular measurements. Indeed, since the development of refractive surgery including all the techniques dedicated to the correction of refractive errors, as well as the emergence of intraocular lens (IOL), ophthalmic surgeons have to monitor overall acceptance as well as secondary effects related to these implants on the structures of the anterior eye segment. High frequency ultrasound imaging provides the required spatial resolution for this task. However, the development of 3D ultrasound imaging allows for the development of new applications in ophthalmology, for instance pre-operative dimensioning of the lens. 3D modelling of the anterior eye segment therefore allows studying the IOL behaviour and may help designing future personalized IOL tailored for each patient. Within this context, we present an original 3D segmentation and reconstruction method based on 3D models registration, dedicated to the anterior eye segment acquired in high frequency ultrasound imaging. We used a 3D ultrasound free-hand acquisition system, composed of a high frequency ultrasound probe and a localization module based on a camera and infrared markers. This 3D ultrasound system provides images along with associated 3D spatial positioning information. We were therefore able to develop an entire ultrasound images acquisition and processing chain. This allowed us creating realistic reference 3D models from sequences of ultrasound images of the anterior eye segment. We thus propose a method based on the iterative closest point (ICP) algorithm for the registration of the 3D reference models to 3D ultrasound acquired data. We have also selected and adapted various methods for the evaluation of the proposed reconstruction process. These methods highlight the accuracy of the obtained reconstructions.
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Study and optimization of 2D matrix arrays for 3D ultrasound imaging / Etude et optimisation de sondes matricielles 2D pour l'imagerie ultrasonore 3DDiarra, Bakary 11 October 2013 (has links)
L’imagerie échographique en trois dimensions (3D) est une modalité d’imagerie médicale en plein développement. En plus de ses nombreux avantages (faible cout, absence de rayonnement ionisant, portabilité) elle permet de représenter les structures anatomiques dansleur forme réelle qui est toujours 3D. Les sondes à balayage mécaniques, relativement lentes, tendent à être remplacées par des sondes bidimensionnelles ou matricielles qui sont unprolongement dans les deux directions, latérale et azimutale, de la sonde classique 1D. Cetagencement 2D permet un dépointage du faisceau ultrasonore et donc un balayage 3D del’espace. Habituellement, les éléments piézoélectriques d’une sonde 2D sont alignés sur unegrille et régulièrement espacés d’une distance (en anglais le « pitch ») soumise à la loi del’échantillonnage spatial (distance inter-élément inférieure à la demi-longueur d’onde) pour limiter l’impact des lobes de réseau. Cette contrainte physique conduit à une multitude d’éléments de petite taille. L’équivalent en 2D d’une sonde 1D de 128 éléments contient128x128=16 384 éléments. La connexion d’un nombre d’éléments aussi élevé constitue unvéritable défi technique puisque le nombre de canaux dans un échographe actuel n’excède querarement les 256. Les solutions proposées pour contrôler ce type de sonde mettent en oeuvredu multiplexage ou des techniques de réduction du nombre d’éléments, généralement baséessur une sélection aléatoire de ces éléments (« sparse array »). Ces méthodes souffrent dufaible rapport signal à bruit du à la perte d’énergie qui leur est inhérente. Pour limiter cespertes de performances, l’optimisation reste la solution la plus adaptée. La première contribution de cette thèse est une extension du « sparse array » combinéeavec une méthode d’optimisation basée sur l’algorithme de recuit simulé. Cette optimisation permet de réduire le nombre nécessaire d’éléments à connecter en fonction des caractéristiques attendues du faisceau ultrasonore et de limiter la perte d’énergie comparée à la sonde complète de base. La deuxième contribution est une approche complètement nouvelle consistant à adopter un positionnement hors grille des éléments de la sonde matricielle permettant de supprimer les lobes de réseau et de s’affranchir de la condition d’échantillonnage spatial. Cette nouvelles tratégie permet d’utiliser des éléments de taille plus grande conduisant ainsi à un nombre d’éléments nécessaires beaucoup plus faible pour une même surface de sonde. La surface active de la sonde est maximisée, ce qui se traduit par une énergie plus importante et donc unemeilleure sensibilité. Elle permet également de balayer un angle de vue plus important, leslobes de réseau étant très faibles par rapport au lobe principal. Le choix aléatoire de la position des éléments et de leur apodization (ou pondération) reste optimisé par le recuit simulé.Les méthodes proposées sont systématiquement comparées avec la sonde complète dansle cadre de simulations numériques dans des conditions réalistes. Ces simulations démontrent un réel potentiel pour l’imagerie 3D des techniques développées. Une sonde 2D de 8x24=192 éléments a été construite par Vermon (Vermon SA, ToursFrance) pour tester les méthodes de sélection des éléments développées dans un cadreexpérimental. La comparaison entre les simulations et les résultats expérimentaux permettentde valider les méthodes proposées et de prouver leur faisabilité. / 3D Ultrasound imaging is a fast-growing medical imaging modality. In addition to its numerous advantages (low cost, non-ionizing beam, portability) it allows to represent the anatomical structures in their natural form that is always three-dimensional. The relativelyslow mechanical scanning probes tend to be replaced by two-dimensional matrix arrays that are an extension in both lateral and elevation directions of the conventional 1D probe. This2D positioning of the elements allows the ultrasonic beam steering in the whole space. Usually, the piezoelectric elements of a 2D array probe are aligned on a regular grid and spaced out of a distance (the pitch) subject to the space sampling law (inter-element distancemust be shorter than a mid-wavelength) to limit the impact of grating lobes. This physical constraint leads to a multitude of small elements. The equivalent in 2D of a 1D probe of 128elements contains 128x128 = 16,384 elements. Connecting such a high number of elements is a real technical challenge as the number of channels in current ultrasound scanners rarely exceeds 256. The proposed solutions to control this type of probe implement multiplexing or elements number reduction techniques, generally using random selection approaches (« spars earray »). These methods suffer from low signal to noise ratio due to the energy loss linked to the small number of active elements. In order to limit the loss of performance, optimization remains the best solution. The first contribution of this thesis is an extension of the « sparse array » technique combined with an optimization method based on the simulated annealing algorithm. The proposed optimization reduces the required active element number according to the expected characteristics of the ultrasound beam and permits limiting the energy loss compared to the initial dense array probe.The second contribution is a completely new approach adopting a non-grid positioningof the elements to remove the grating lobes and to overstep the spatial sampling constraint. This new strategy allows the use of larger elements leading to a small number of necessaryelements for the same probe surface. The active surface of the array is maximized, whichresults in a greater output energy and thus a higher sensitivity. It also allows a greater scansector as the grating lobes are very small relative to the main lobe. The random choice of the position of the elements and their apodization (or weighting coefficient) is optimized by the simulated annealing.The proposed methods are systematically compared to the dense array by performing simulations under realistic conditions. These simulations show a real potential of the developed techniques for 3D imaging.A 2D probe of 8x24 = 192 elements was manufactured by Vermon (Vermon SA, Tours,France) to test the proposed methods in an experimental setting. The comparison between simulation and experimental results validate the proposed methods and prove their feasibility. / L'ecografia 3D è una modalità di imaging medicale in rapida crescita. Oltre ai vantaggiin termini di prezzo basso, fascio non ionizzante, portabilità, essa permette di rappresentare le strutture anatomiche nella loro forma naturale, che è sempre tridimensionale. Le sonde ascansione meccanica, relativamente lente, tendono ad essere sostituite da quelle bidimensionali che sono una estensione in entrambe le direzioni laterale ed azimutale dellasonda convenzionale 1D. Questo posizionamento 2D degli elementi permette l'orientamentodel fascio ultrasonico in tutto lo spazio. Solitamente, gli elementi piezoelettrici di una sondamatriciale 2D sono allineati su una griglia regolare e separati da una distanza (detta “pitch”) sottoposta alla legge del campionamento spaziale (la distanza inter-elemento deve esseremeno della metà della lunghezza d'onda) per limitare l'impatto dei lobi di rete. Questo vincolo fisico porta ad una moltitudine di piccoli elementi. L'equivalente di una sonda 1D di128 elementi contiene 128x128 = 16.384 elementi in 2D. Il collegamento di un così grandenumero di elementi è una vera sfida tecnica, considerando che il numero di canali negliecografi attuali supera raramente 256. Le soluzioni proposte per controllare questo tipo disonda implementano le tecniche di multiplazione o la riduzione del numero di elementi, utilizzando un metodo di selezione casuale (« sparse array »). Questi metodi soffrono di unbasso rapporto segnale-rumore dovuto alla perdita di energia. Per limitare la perdita di prestazioni, l’ottimizzazione rimane la soluzione migliore. Il primo contributo di questa tesi è un’estensione del metodo dello « sparse array » combinato con un metodo di ottimizzazione basato sull'algoritmo del simulated annealing. Questa ottimizzazione riduce il numero degli elementi attivi richiesto secondo le caratteristiche attese del fascio di ultrasuoni e permette di limitare la perdita di energia.Il secondo contributo è un approccio completamente nuovo, che propone di adottare un posizionamento fuori-griglia degli elementi per rimuovere i lobi secondari e per scavalcare il vincolo del campionamento spaziale. Questa nuova strategia permette l'uso di elementi piùgrandi, riducendo così il numero di elementi necessari per la stessa superficie della sonda. La superficie attiva della sonda è massimizzata, questo si traduce in una maggiore energia equindi una maggiore sensibilità. Questo permette inoltre la scansione di un più grande settore,in quanto i lobi secondari sono molto piccoli rispetto al lobo principale. La scelta casualedella posizione degli elementi e la loro apodizzazione viene ottimizzata dal simulate dannealing. I metodi proposti sono stati sistematicamente confrontati con la sonda completaeseguendo simulazioni in condizioni realistiche. Le simulazioni mostrano un reale potenzialedelle tecniche sviluppate per l'imaging 3D.Una sonda 2D di 8x24 = 192 elementi è stata fabbricata da Vermon (Vermon SA, ToursFrance) per testare i metodi proposti in un ambiente sperimentale. Il confronto tra lesimulazioni e i risultati sperimentali ha permesso di convalidare i metodi proposti edimostrare la loro fattibilità.
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Segmentation of 3D Carotid Ultrasound Images Using Weak Geometric PriorsSolovey, Igor January 2010 (has links)
Vascular diseases are among the leading causes of death in Canada and around the globe. A major underlying cause of most such medical conditions is atherosclerosis, a gradual accumulation of plaque on the walls of blood vessels. Particularly vulnerable to atherosclerosis is the carotid artery, which carries blood to the brain. Dangerous narrowing of the carotid artery can lead to embolism, a dislodgement of plaque fragments which travel to the brain and are the cause of most strokes. If this pathology can be detected early, such a deadly scenario can be potentially prevented through treatment or surgery. This not only improves the patient's prognosis, but also dramatically lowers the overall cost of their treatment.
Medical imaging is an indispensable tool for early detection of atherosclerosis, in particular since the exact location and shape of the plaque need to be known for accurate diagnosis. This can be achieved by locating the plaque inside the artery and measuring its volume or texture, a process which is greatly aided by image segmentation. In particular, the use of ultrasound imaging is desirable because it is a cost-effective and safe modality. However, ultrasonic images depict sound-reflecting properties of tissue, and thus suffer from a number of unique artifacts not present in other medical images, such as acoustic shadowing, speckle noise and discontinuous tissue boundaries. A robust ultrasound image segmentation technique must take these properties into account.
Prior to segmentation, an important pre-processing step is the extraction of a series of features from the image via application of various transforms and non-linear filters. A number of such features are explored and evaluated, many of them resulting in piecewise smooth images. It is also proposed to decompose the ultrasound image into several statistically distinct components. These components can be then used as features directly, or other features can be obtained from them instead of the original image. The decomposition scheme is derived using Maximum-a-Posteriori estimation framework and is efficiently computable.
Furthermore, this work presents and evaluates an algorithm for segmenting the carotid artery in 3D ultrasound images from other tissues. The algorithm incorporates information from different sources using an energy minimization framework. Using the ultrasound image itself, statistical differences between the region of interest and its background are exploited, and maximal overlap with strong image edges encouraged. In order to aid the convergence to anatomically accurate shapes, as well as to deal with the above-mentioned artifacts, prior knowledge is incorporated into the algorithm by using weak geometric priors. The performance of the algorithm is tested on a number of available 3D images, and encouraging results are obtained and discussed.
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Segmentation of 3D Carotid Ultrasound Images Using Weak Geometric PriorsSolovey, Igor January 2010 (has links)
Vascular diseases are among the leading causes of death in Canada and around the globe. A major underlying cause of most such medical conditions is atherosclerosis, a gradual accumulation of plaque on the walls of blood vessels. Particularly vulnerable to atherosclerosis is the carotid artery, which carries blood to the brain. Dangerous narrowing of the carotid artery can lead to embolism, a dislodgement of plaque fragments which travel to the brain and are the cause of most strokes. If this pathology can be detected early, such a deadly scenario can be potentially prevented through treatment or surgery. This not only improves the patient's prognosis, but also dramatically lowers the overall cost of their treatment.
Medical imaging is an indispensable tool for early detection of atherosclerosis, in particular since the exact location and shape of the plaque need to be known for accurate diagnosis. This can be achieved by locating the plaque inside the artery and measuring its volume or texture, a process which is greatly aided by image segmentation. In particular, the use of ultrasound imaging is desirable because it is a cost-effective and safe modality. However, ultrasonic images depict sound-reflecting properties of tissue, and thus suffer from a number of unique artifacts not present in other medical images, such as acoustic shadowing, speckle noise and discontinuous tissue boundaries. A robust ultrasound image segmentation technique must take these properties into account.
Prior to segmentation, an important pre-processing step is the extraction of a series of features from the image via application of various transforms and non-linear filters. A number of such features are explored and evaluated, many of them resulting in piecewise smooth images. It is also proposed to decompose the ultrasound image into several statistically distinct components. These components can be then used as features directly, or other features can be obtained from them instead of the original image. The decomposition scheme is derived using Maximum-a-Posteriori estimation framework and is efficiently computable.
Furthermore, this work presents and evaluates an algorithm for segmenting the carotid artery in 3D ultrasound images from other tissues. The algorithm incorporates information from different sources using an energy minimization framework. Using the ultrasound image itself, statistical differences between the region of interest and its background are exploited, and maximal overlap with strong image edges encouraged. In order to aid the convergence to anatomically accurate shapes, as well as to deal with the above-mentioned artifacts, prior knowledge is incorporated into the algorithm by using weak geometric priors. The performance of the algorithm is tested on a number of available 3D images, and encouraging results are obtained and discussed.
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