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Cardiovascular diseases (CVDs) constitute a leading cause of death, including premature death, in the developed world. The early diagnosis and treatment of CVDs is therefore of great importance. Modern imaging modalities enable the quantification and analysis of the cardiovascular system and provide researchers and clinicians with valuable tools for the diagnosis and treatment of CVDs. In particular, echocardiography offers a number of advantages, compared to other imaging modalities, making it a prevalent tool for assessing cardiac morphology and function. However, cardiac ultrasound images can suffer from a range of artifacts reducing their image quality and diagnostic value. As a result, there is great interest in the development of processing techniques that address such limitations. This thesis introduces and quantitatively evaluates four methods that enhance clinical cardiac ultrasound data by utilising information which until now has been predominantly disregarded. All methods introduced in this thesis utilise multiple partially uncorrelated instances of a cardiac cycle in order to acquire the information required to suppress or enhance certain image features. No filtering out of information is performed at any stage throughout the processing. This constitutes the main differentiation to previous data enhancement approaches which tend to filter out information based on some static or adaptive selection criteria. The first two image enhancement methods utilise spatial averaging of partially uncorrelated data acquired through a single acoustic window. More precisely, Temporal Compounding enhances cardiac ultrasound data by averaging partially uncorrelated instances of the imaged structure acquired over a number of consecutive cardiac cycles. An extension to the notion of spatial compounding of cardiac ultrasound data is 3D-to-2D Compounding, which presents a novel image enhancement method by acquiring and compounding spatially adjacent (along the elevation plane), partially uncorrelated, 2D slices of the heart extracted as a thin angular sub-sector of a volumetric pyramid scan. Data enhancement introduced by both approaches includes the substantial suppression of tissue speckle and cavity noise. Furthermore, by averaging decorrelated instances of the same cardiac structure, both compounding methods can enhance tissue structures, which are masked out by high levels of noise and shadowing, increasing their corresponding tissue/cavity detectability. The third novel data enhancement approach, referred as Dynamic Histogram Based Intensity Mapping (DHBIM), investigates the temporal variations within image histograms of consecutive frames in order to (i) identify any unutilised/underutilised intensity levels and (ii) derive the tissue/cavity intensity threshold within the processed frame sequence. Piecewise intensity mapping is then used to enhance cardiac ultrasound data. DHBIM introduces cavity noise suppression, enhancement of tissue speckle information as well as considerable increase in tissue/cavity contrast and detectability. A data acquisition and analysis protocol for integrating the dynamic intensity mapping along with spatial compounding methods is also investigated. The linear integration of DHBIM and Temporal Compounding forms the fourth and final implemented method, which is also quantitatively assessed. By taking advantage of the benefits and compensating for the limitations of each individual method, the integrated method suppresses cavity noise and tissue speckle while enhancing tissue/cavity contrast as well as the delineation of cardiac tissue boundaries even when heavily corrupted by cardiac ultrasound artifacts. Finally, a novel protocol for the quantitative assessment of the effect of each data enhancement method on image quality and diagnostic value is employed. This enables the quantitative evaluation of each method as well as the comparison between individual methods using clinical data from 32 patients. Image quality is assessed using a range of quantitative measures such as signal-to-noise ratio, tissue/cavity contrast and detectability index. Diagnostic value is assessed through variations in the repeatability level of routine clinical measurements performed on patient cardiac ultrasound scans by two experienced echocardiographers. Commonly used clinical measures such as the wall thickness of the Interventricular Septum (IVS) and the Left Ventricle Posterior Wall (LVPW) as well as the cavity diameter of the Left Ventricle (LVID) and Left Atrium (LAD) are employed for assessing diagnostic value.

Conventional ultrasonographic examination of the bovine ovary is based on a sequence of two-dimensional (2D) cross-section images. Day-to-day estimation of the number, size, shape and position of the ovarian follicles is one of the most important aspects of ovarian research. Computer-assisted follicle segmentation of ovarian volume can relieve physicians from the tedious manual detection of follicles, provide objective assessment of spatial relationships between the ovarian structures and therefore has the potential to improve accuracy. Modern segmentation procedures are performed on 2D images and the three-dimensional (3D) visualization of follicles is obtained from the reconstruction of a sequence of 2D segmented follicles. <p>The objective of this study was to develop a semi-automatic 3D follicle segmentation method based on seeded region growing. The 3D datasets were acquired from a sequence of 2D ultrasound images and the ovarian structures were segmented from the reconstructed ovarian volume in a single step. A seed is placed manually in each follicle and the growth of the seed is controlled by the algorithm using a combination of average grey-level, standard deviation of the intensity, newly-developed volumetric comparison test and a termination criterion. One important contribution of this algorithm is that it overcomes the boundary leakage problem of follicles of conventional 2D segmentation procedures. The results were validated against the aspiration volume of follicles, the manually detected follicles by an expert and an existing algorithm.<p>We anticipate that this algorithm will enhance follicular assessment based on current ultrasound techniques in cases when large numbers of follicles (e.g. ovarian superstimulation) obviate accurate counting and size measurement.

Conventional ultrasonographic examination of the bovine ovary is based on a sequence of two-dimensional (2D) cross-section images. Day-to-day estimation of the number, size, shape and position of the ovarian follicles is one of the most important aspects of ovarian research. Computer-assisted follicle segmentation of ovarian volume can relieve physicians from the tedious manual detection of follicles, provide objective assessment of spatial relationships between the ovarian structures and therefore has the potential to improve accuracy. Modern segmentation procedures are performed on 2D images and the three-dimensional (3D) visualization of follicles is obtained from the reconstruction of a sequence of 2D segmented follicles. <p>The objective of this study was to develop a semi-automatic 3D follicle segmentation method based on seeded region growing. The 3D datasets were acquired from a sequence of 2D ultrasound images and the ovarian structures were segmented from the reconstructed ovarian volume in a single step. A seed is placed manually in each follicle and the growth of the seed is controlled by the algorithm using a combination of average grey-level, standard deviation of the intensity, newly-developed volumetric comparison test and a termination criterion. One important contribution of this algorithm is that it overcomes the boundary leakage problem of follicles of conventional 2D segmentation procedures. The results were validated against the aspiration volume of follicles, the manually detected follicles by an expert and an existing algorithm.<p>We anticipate that this algorithm will enhance follicular assessment based on current ultrasound techniques in cases when large numbers of follicles (e.g. ovarian superstimulation) obviate accurate counting and size measurement.

Orientador: Maria Jaqueline Mamprim / Banca: Maria Denise Lopes / Banca: Geórgia Bignardi Jarreta / Resumo: Nenhuma avaliação clínica ou a receptividade à cobertura pelo macho é suficientemente rigorosa para detectar com exatidão a ocorrência e o dia das ovulações nas cadelas. Algumas cadelas podem ovular no quinto dia do ciclo estral, enquanto outras, ovulam mais tardiamnente, como no trigésimo dia. A técnica mais recente para determinar a ovulação na cadela é a exploração ovariana por ultrasonografia. Portanto, o presente trabalho tem por objetivo avaliar o grau de confiabilidade e rigor do exame ultra-sonográfico, em modo B e a possibilidade de avaliações dopplerfluxométricas de artérias intra-ovarianas para uma detecção segura da ovulação nas cadelas. Para tanto foram utilizadas 5 cadelas, SRD, adultas, com peso de até 10 Kg e em início de fase folicular do ciclo estral. Durante a fase de proestro e estro foram realizados exames ultra-sonográficos (Logic 3, GE) com transdutor de 10Mhz, seriados, com no máximo 48horas de intervalo. Foram realizados cortes sagitais e transversais para se detectar e mensurar os folículos ovarianos. A partir da detecção do colapso folicular ou da substituição da imagem circunscrita anecóica de parede regular por uma estrutura hipoecogênica de contornos irregulares foi monitorado o início de formação luteal. Na fase luteal do ciclo foram realizadas mensurações dos corpos lúteos. Foram realizadas também imagens com o doppler colorido e espectral. Para avaliação do Doppler espectral o cursor foi colocado sobre a artéria ângulo insonação 60º, procedendo-se a avaliação da velocidade máxima do pico sistólico (VPS), dos índices de resistividade (IR) e pulsatilidade (IP). Foi realizada uma análise descritiva dos resultados obtidos. Pela imagem ultra-sonográfica convencional foi possível detectar 100% dos ovários das cadelas estudadas, possibilitando acompanhar o desenvolvimento folicular, colapso e formação... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: No clinical evaluation or the receptivity to the male can be rigorous enough to detect precisely the occurrence and the day of the ovulations in dogs. Some dogs can ovulate on the fifth day of the estral cycle, while others, ovulate later, on the thirtieth day. The latest technique to determine the ovulation in dogs is the ovarian exploration with ultrasound. Therefore, the present work evaluates the degree of dependability and accuracy of the ultrasound examination, in B mode and the possibility of dopplerfluxometric evaluations of intra-ovarian arteries for a safe detection of the ovulation in dogs. Therefore 5 mongrel adult bitches, with weight of up to 10 kg and at the onset of follicular phase, were used. During proestrus and estrus ultrasound examinations (Logic 3, GE) with transducer of 10Mhz were carried out in series with the maximum of 48-hour intervals. Sagittal and transversal cuts were taken to detect and measure the ovarian follicules. From the detection of the folicular collapse or the substitution of the anecoiccircumscribed image of regular wall for a hipoecogenic structure of irregular outline was monitored the beginning of luteal formation. In the luteal phase of the cycle measurements of the luteum bodies were carried out. Images with the spectral doppler had been carried also through colorful and. For evaluation of the spectral Doppler the cursor was placed on the artery angle insonation = 60º, proceeding it evaluation from the maximum speed of the systolic peak (SSP), of the resistivity rate (RR) and pulsatility rate (PR). A descriptive analysis of the results was carried out. For the conventional ultrasound image it was possible to detect 100% of the ovarius of the studied dogs, making possible to follow the development of the follicule, collapse and formation of luteum body in 85.7% of the follicules. The presence of luteum bodies was identified in 100% of the... (Complete abstract click electronic access below) / Mestre

Made available in DSpace on 2014-06-11T19:30:11Z (GMT). No. of bitstreams: 0 Previous issue date: 2008-06-05Bitstream added on 2014-06-13T20:07:36Z : No. of bitstreams: 1 bicudo_alc_dr_botfmvz.pdf: 403167 bytes, checksum: 90885c2effdcd34acfe70d5474be4d99 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Nenhuma avaliação clínica ou a receptividade à cobertura pelo macho é suficientemente rigorosa para detectar com exatidão a ocorrência e o dia das ovulações nas cadelas. Algumas cadelas podem ovular no quinto dia do ciclo estral, enquanto outras, ovulam mais tardiamnente, como no trigésimo dia. A técnica mais recente para determinar a ovulação na cadela é a exploração ovariana por ultrasonografia. Portanto, o presente trabalho tem por objetivo avaliar o grau de confiabilidade e rigor do exame ultra-sonográfico, em modo B e a possibilidade de avaliações dopplerfluxométricas de artérias intra-ovarianas para uma detecção segura da ovulação nas cadelas. Para tanto foram utilizadas 5 cadelas, SRD, adultas, com peso de até 10 Kg e em início de fase folicular do ciclo estral. Durante a fase de proestro e estro foram realizados exames ultra-sonográficos (Logic 3, GE) com transdutor de 10Mhz, seriados, com no máximo 48horas de intervalo. Foram realizados cortes sagitais e transversais para se detectar e mensurar os folículos ovarianos. A partir da detecção do colapso folicular ou da substituição da imagem circunscrita anecóica de parede regular por uma estrutura hipoecogênica de contornos irregulares foi monitorado o início de formação luteal. Na fase luteal do ciclo foram realizadas mensurações dos corpos lúteos. Foram realizadas também imagens com o doppler colorido e espectral. Para avaliação do Doppler espectral o cursor foi colocado sobre a artéria ângulo insonação ≤ 60º, procedendo-se a avaliação da velocidade máxima do pico sistólico (VPS), dos índices de resistividade (IR) e pulsatilidade (IP). Foi realizada uma análise descritiva dos resultados obtidos. Pela imagem ultra-sonográfica convencional foi possível detectar 100% dos ovários das cadelas estudadas, possibilitando acompanhar o desenvolvimento folicular, colapso e formação de corpo lúteo em 85,7% dos folículos. A presença de corpos lúteos foi identificada em 100% das cadelas. A média da velocidade máxima do pico sistólico foi de 26,41cm/s, observada desde 120horas até 24horas após a ovulação. O IR apresentou declínio no dia da ovulação ou 24horas após, e o seu valor variou de 0,44 – 0,59 neste período. O IP apresentou muitas oscilações durante o proestro e estro, apresentando declínio desde 120horas antes até 24horas após a ovulação e seu valor nesse período foi de 0,57-1,1. / No clinical evaluation or the receptivity to the male can be rigorous enough to detect precisely the occurrence and the day of the ovulations in dogs. Some dogs can ovulate on the fifth day of the estral cycle, while others, ovulate later, on the thirtieth day. The latest technique to determine the ovulation in dogs is the ovarian exploration with ultrasound. Therefore, the present work evaluates the degree of dependability and accuracy of the ultrasound examination, in B mode and the possibility of dopplerfluxometric evaluations of intra-ovarian arteries for a safe detection of the ovulation in dogs. Therefore 5 mongrel adult bitches, with weight of up to 10 kg and at the onset of follicular phase, were used. During proestrus and estrus ultrasound examinations (Logic 3, GE) with transducer of 10Mhz were carried out in series with the maximum of 48-hour intervals. Sagittal and transversal cuts were taken to detect and measure the ovarian follicules. From the detection of the folicular collapse or the substitution of the anecoiccircumscribed image of regular wall for a hipoecogenic structure of irregular outline was monitored the beginning of luteal formation. In the luteal phase of the cycle measurements of the luteum bodies were carried out. Images with the spectral doppler had been carried also through colorful and. For evaluation of the spectral Doppler the cursor was placed on the artery angle insonation = 60º, proceeding it evaluation from the maximum speed of the systolic peak (SSP), of the resistivity rate (RR) and pulsatility rate (PR). A descriptive analysis of the results was carried out. For the conventional ultrasound image it was possible to detect 100% of the ovarius of the studied dogs, making possible to follow the development of the follicule, collapse and formation of luteum body in 85.7% of the follicules. The presence of luteum bodies was identified in 100% of the dogs. The average of the maximum speed of the systolic peak was of 26.41cm/s, observed since 120 hours until 24hours after the ovulation. RR presented decline on the day of the ovulation or 24 hours, and its value varied 0.44 - 0.59 in this period. The PR presented many oscillations during proestrus and estrus, presenting decline from 120 hours before until 24horas after the ovulation and its value in this period was of 0.57-1.1.

La maladie veineuse thromboembolique (MVTE) est un problème de santé publique (plus de 100000 cas par an en France). Elle regroupe deux entités cliniques : la thrombose veineuse profonde (TVP) des membres inférieurs et l’embolie pulmonaire (EP). La TVP correspond à la formation inadaptée d’un thrombus veineux (appelé aussi caillot sanguin) dans les veines profondes (poplitées, fémorales, iliaques). Un thrombus est principalement constitué de globules rouges et de plaquettes dans un réseau de fibrine. La complication majeure d’une TVP est la survenue d’une EP, c’est-à-dire que le thrombus s’est détaché de la paroi veineuse, ou s’est fragmenté, et est entraîné par la circulation sanguine jusqu’à une artère pulmonaire. Cette complication a un taux de mortalité assez élevée autour de 10000 à 20000 cas mortels par an en France. La survenue d’une TVP est multifactorielle associant des facteurs génétiques et acquis pouvant être répartis en trois catégories : la stase veineuse, l’altération de la paroi d’une veine et une hypercoagulabilité. En analysant la structure du thrombus, notre projet vise à identifier le facteur principal responsable de la TVP et à évaluer le risque d’EP. Pour caractériser sa structure, nous disposons de deux modes d’imagerie acoustique : l’échographie et l’élastographie (carte de dureté). Nous proposons d’extraire des descripteurs de ces images acoustiques par deux approches, l’une basée sur les ondelettes (le scattering operator) et l’autre sur les statistiques d’ordre supérieur (les multicorrélations). Ces descripteurs sont ensuite analysées par diverses techniques de classification (analyse en composantes principales, k-moyennes, classification spectrale) pour retrouver la cause principale des TVP ou la présence d’EP. / Venous thromboembolism (VTE) is an important public health issue (over 100000 individuals in France per year). VTE is a combination of a deep venous thrombosis (DVT) and a pulmonary embolism (PE). DVT is an inappropriate formation of a thrombus (also called blood clot) in one of the deep veins of the body, usually in the leg (popliteal, femoral, iliac). There are mainly three components in a thrombus: platelets, red blood cells and a mesh of fibrins. The main complication of a DVT is a pulmonary embolism (PE) which occurs when a thrombus breaks loose and travels to the lungs. PE affects an estimated 10000 - 20 000 individuals just in France per year. Three physiopathological mechanisms cancontribute, isolated or combined, to the development of a DVT: venous stasis, endothelial injury and hypercoagulability. Our project is aiming to relate the thrombus structure, its main triggering factor and the risk of a PE. To characterize the thrombus structure, we are collecting ultrasonography (echogenicity) and elastography (stiffness) of human thrombus. We propose to extract features from these to kind of ultrasound images using two approaches: one basedon wavelets (the scattering operator) and another based on high order statistics (multicorrelations). Then, the obtained features are analysed using several classification technics (principal component analysis, k-means, spectral clustering) to find the main cause of the DVT or the presence of PE.

Optimal surface finding (OSF), a graph-based optimization approach to image segmentation, represents a powerful framework for medical image segmentation and analysis. In many applications, a pre-segmentation is required to enable OSF graph construction. Also, the cost function design is critical for the success of OSF. In this thesis, two issues in the context of OSF segmentation are addressed. First, a robust model-based segmentation method suitable for OSF initialization is introduced. Second, an OSF-based segmentation refinement approach is presented. For segmenting complex anatomical structures (e.g., lungs), a rough initial segmentation is required to apply an OSF-based approach. For this purpose, a novel robust active shape model (RASM) is presented. The RASM matching in combination with OSF is investigated in the context of segmenting lungs with large lung cancer masses in 3D CT scans. The robustness and effectiveness of this approach is demonstrated on 30 lung scans containing 20 normal lungs and 40 diseased lungs where conventional segmentation methods frequently fail to deliver usable results. The developed RASM approach is generally applicable and suitable for large organs/structures. While providing high levels of performance in most cases, OSF-based approaches may fail in a local region in the presence of pathology or other local challenges. A new (generic) interactive refinement approach for correcting local segmentation errors based on the OSF segmentation framework is proposed. Following the automated segmentation, the user can inspect the result and correct local or regional segmentation inaccuracies by (iteratively) providing clues regarding the location of the correct surface. This expert information is utilized to modify the previously calculated cost function, locally re-optimizing the underlying modified graph without a need to start the new optimization from scratch. For refinement, a hybrid desktop/virtual reality user interface based on stereoscopic visualization technology and advanced interaction techniques is utilized for efficient interaction with the segmentations (surfaces). The proposed generic interactive refinement method is adapted to three applications. First, two refinement tools for 3D lung segmentation are proposed, and the performance is assessed on 30 test cases from 18 CT lung scans. Second, in a feasibility study, the approach is expanded to 4D OSF-based lung segmentation refinement and an assessment of performance is provided. Finally, a dual-surface OSF-based intravascular ultrasound (IVUS) image segmentation framework is introduced, application specific segmentation refinement methods are developed, and an evaluation on 41 test cases is presented. As demonstrated by experiments, OSF-based segmentation refinement is a promising approach to address challenges in medical image segmentation.

The thesis focuses on the measurement of intima media thickness, which seems to be a significant marker of the risk of cardiovascular events. Intima media thickness is measured in ultrasound image displaying the common carotid artery in its longitudinal section. In the longitudinal section the intima and media layers are visible. Thesis is discussing both technical and medical background and summarizes state of the art in this field. The main part of the thesis describes the novel automatic system for measurement of intima media thickness. Proposed system includes also robust method for artery localization and therefore is able to process raw B-mode data from ultrasound station without any initialization or manual preprocessing.

Le travail présenté dans cette thèse porte principalement sur le développement de méthodes permettant d'extraire des descripteurs pertinents des images acquises des articulateurs dans les chants rares : les polyphonies traditionnelles Corses, Sardes, la musique Byzantine, ainsi que le Human Beat Box. Nous avons collecté des données, et employons des méthodes d'apprentissage statistique pour les modéliser, notamment les méthodes récentes d'apprentissage profond (Deep Learning).Nous avons étudié dans un premier temps des séquences d'images échographiques de la langue apportant des informations sur l'articulation, mais peu lisibles sans connaissance spécialisée en échographie. Nous avons développé des méthodes pour extraire de façon automatique le contour supérieur de la langue montré par les images échographiques. Nos travaux ont donné des résultats d'extraction du contour de la langue comparables à ceux obtenus dans la littérature, ce qui pourrait permettre des applications en pédagogie du chant.Ensuite, nous avons prédit l'évolution des paramètres du filtre qu'est le conduit vocal depuis des séquences d'images de langue et de lèvres, sur des bases de données constituées de voyelles isolées puis de chants traditionnels Corses. L'utilisation des paramètres du filtre du conduit vocal, combinés avec le développement d'un modèle acoustique de source vocale exploitant l'enregistrement électroglottographique, permet de synthétiser des extraits de voix chantée en utilisant les images articulatoires (de la langue et des lèvres)et l'activité glottique, avec des résultats supérieurs à ceux obtenus avec les techniques existant dans la littérature. / This thesis reports newly developed methods which can be applied to extract relevant features from articulator images in rare singing: traditional Corsican and Sardinian polyphonies, Byzantine music, as well as Human Beat Box. We collected data, and modeled these using machine learning methods, specifically novel deep learning methods. We first modelled tongue ultrasound image sequences, carrying relevant articulatory information which would otherwise be difficult to interpret without specialized skills in ultrasound imaging. We developed methods to extract automatically the superior contour of the tongue displayed on ultrasound images. Our tongue contour extraction results are comparable with those obtained in the literature, which could lead to applications in singing pedagogy. Afterwards, we predicted the evolution of the vocal tract filter parameters from sequences of tongue and lip images, first on isolated vowel databases then on traditional Corsican singing. Applying the predicted filter parameters, combined with the development of a vocal source acoustic model exploiting electroglottographic recordings, allowed us to synthesize singing voice excerpts using articulatory images (of tongue and lips) and glottal activity, with results superior to those obtained using existing technics reported in the literature.