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1

Mazinani, Mahdi. "Computer aided detection and measurement of coronary artery disease from computed tomography angiography images." Thesis, Kingston University, 2012. http://eprints.kingston.ac.uk/24527/.

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Coronary artery disease is one of the most pernicious diseases around the world and early identification of vascular disease can help to reduce morbidity and mortality. Assessment of the degree of vascular obstruction, or stenosis, is critical for classifying the risks of the future vascular events. Automatic detection and quantification of stenosis are important in assessing coronary artery disease from medical imagery, especially for disease progression. Important factors affecting the reproducability and robustness of accuarate quantification arise from the partial volume effect and other n
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Mazeyev, Yuri. "Direction estimation on 3D-tomography images of jawbones." Thesis, Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-1661.

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<p>The present work expose a technique of estimation of optimal direction for placing dental implant. A volumetric computed tomography (CT) scan is used as a help of the following searches. The work offers criteria of the optimal implant placement direction and methods of evaluation on direction’s significance. The technique utilizes structure tensor to find a normal to the jawbone surface. Direction of that normal is then used as initial direction for search of optimal direction.</p><p>The technique described in the present work aimed to support doctor’s decisions during dental implantation t
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Pivot, Odran. "Scatter correction for spectral computed tomography." Thesis, Lyon, 2019. http://www.theses.fr/2019LYSEI102.

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Le rayonnement diffusé est une cause majeure de biais, de baisse de contraste et d'artéfacts en tomographie par rayons x. De nombreuses méthode de correction ont été proposées pour la tomographie conventionnelle (utilisant des détecteurs à intégration en énergie) mais le sujet reste ouvert dans le cadre de l'imagerie spectrale, une nouvelle modalité d'imagerie basée sur l'utilisation de détecteurs à comptage des photons résolus en énergie. L'objectif principal de ce travail de thèse a été l'étude de techniques de correction du diffusé adaptées à l'imagerie spectrale. La solution choisie amélio
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Xiang, Jing. "Registration of 3D ultrasound to computed tomography images of the kidney." Thesis, University of British Columbia, 2010. http://hdl.handle.net/2429/27817.

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The integration of 3D computed tomography (CT) and ultrasound (US) is of considerable interest because it can potentially improve many minimally invasive procedures such as robot-assisted laparoscopic partial nephrectomy. Partial nephrectomy patients often receive preoperative CT angiography for diagnosis. The 3D CT image is of high quality and has a large field of view. Intraoperatively, dynamic real-time images are acquired using ultrasound. While US is real-time and safe for frequent imaging, the images captured are noisy and only provide a limited perspective. Providing accurate registrati
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Bazalova, Magdalena. "The use of computed tomography images in Monte Carlo treatment planning." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=32513.

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Monte Carlo (MC) dose calculations cannot accurately assess the dose delivered to the patient during radiotherapy unless the patient anatomy is well known. This thesis focuses on the conversion of patient computed tomography (CT) images into MC geometry files. Metal streaking artifacts and their effect on MC dose calculations are first studied. A correction algorithm is applied to artifact-corrupted images and dose errors due to density and tissue mis-assignment are quantified in a phantom and a patient s
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Udell, Nicholas Philip. "Algorithms for studying murine airway structure in microfocus computed tomography images." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/412643/.

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Complex branching 3D structures, such as root systems, renal vasculature and pulmonary airways and vasculature, are prevalent throughout nature. The analysis and measurement of these structures and the development of automatic or semi-automatic algorithms to study Microfocus Computed Tomography (µCT) images is therefore an important requirement in this field. Asthma is a prevalent chronic airway disease that is not yet fully understood. Murine models of lung diseases are used with increasing frequency. As the lung is a complex 3D structure, there are benefits to using 3D methodology to measure
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Zuluaga, Valencia Maria Alejandra. "Methods for automation of vascular lesions detection in computed tomography images." Thesis, Lyon 1, 2011. http://www.theses.fr/2011LYO10010/document.

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Les travaux de cette thèse sont consacrés à la détection et le diagnostic des lésions vasculaires, particulièrement dans le cas la maladie coronaire. La maladie coronaire continue à être la première cause de mortalité dans les pays industrialisés. En général, l'identification des lésions vasculaires est abordée en essayant de modéliser les anormalités (lésions). Le principal inconvénient de cette approche est que les lésions sont très hétérogènes, ce qui rend difficile la détection de nouvelles lésions qui n'ont pas été prises en compte par le modèle. Dans cette thèse, nous proposons de ne pas
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Zuluaga, Valencia Maria Alejandra. "Methods for automation of vascular lesions detection in computed tomography images." Electronic Thesis or Diss., Lyon 1, 2011. http://www.theses.fr/2011LYO10010.

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Les travaux de cette thèse sont consacrés à la détection et le diagnostic des lésions vasculaires, particulièrement dans le cas la maladie coronaire. La maladie coronaire continue à être la première cause de mortalité dans les pays industrialisés. En général, l'identification des lésions vasculaires est abordée en essayant de modéliser les anormalités (lésions). Le principal inconvénient de cette approche est que les lésions sont très hétérogènes, ce qui rend difficile la détection de nouvelles lésions qui n'ont pas été prises en compte par le modèle. Dans cette thèse, nous proposons de ne pas
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9

Elmshiti, Hashim. "Evaluation of Submandibular Infections using 3-Dimensional Reconstruction of Computed Tomography Images." The Ohio State University, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=osu1452523769.

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Li, Pei. "Automatic interpretation of computed tomography (CT) images for hardwood log defect detection." Thesis, This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-11182008-063222/.

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Staff, Roger T. "The improvement of SPECT images using scatter correction techniques." Thesis, University of Aberdeen, 1994. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU552136.

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The removal of scattered radiation is recognised as one of the major goals to be achieved in SPECT. In this work three scatter removal techniques were investigated. These were dual window scatter subtraction, deconvolution using a Wiener filter and energy weighted acquisition (EWA) using a weighted acquisition module (WAM). In addition to this, the effects of simple background subtraction on SPECT images was also investigated. The techniques were investigated in both a semi-quantitative manner, in terms of the effects of each technique on the cold lesion contrast and image mottle, and qualitat
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Mairhofer, Stefan. "Extracting root system architecture from X-ray micro computed tomography images using visual tracking." Thesis, University of Nottingham, 2014. http://eprints.nottingham.ac.uk/27739/.

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X-ray micro computed tomography (µCT) is increasingly applied in plant biology as an imaging system that is valuable for the study of root development in soil, since it allows the three-dimensional and non-destructive visualisation of plant root systems. Variations in the X-ray attenuation values of root material and the overlap in measured intensity values between roots and soil caused by water and organic matter represent major challenges to the extraction of root system architecture. We propose a novel technique to recover root system information from X-ray CT data, using a strategy based o
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Broyelle, Antoine. "Automated Pulmonary Nodule Detection on Computed Tomography Images with 3D Deep Convolutional Neural Network." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-231930.

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Object detection on natural images has become a single-stage end-to-end process thanks to recent breakthroughs on deep neural networks. By contrast, automated pulmonary nodule detection is usually a three steps method: lung segmentation, generation of nodule candidates and false positive reduction. This project tackles the nodule detection problem with a single stage modelusing a deep neural network. Pulmonary nodules have unique shapes and characteristics which are not present outside of the lungs. We expect the model to capture these characteristics and to only focus on elements inside the l
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Akhtari, Mohammad Mehdi. "Accuracy of inverse treatment planning on computed tomography like images derived from magnetic resonance data." Thesis, Umeå universitet, Institutionen för fysik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-68721.

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Treatment planning for radiotherapy involves different types of imaging to delineate target volume precisely. The most suitable sources to get 3D information of the patient are the computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET)/CT modalities. CT is a modern medical imaging technique that allows three-dimensional treatment planning and conformal treatment techniques. By combining CT images with efficient dosimetry software, accurate patient positioning methods and verification and quality assurance good results can be achieved. The CT images s
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15

Barrera, Cruz Marco Antonio. "Hybrid method algebraic/inverse radon transform for region of interest reconstruction of computed tomography images /." To access this resource online via ProQuest Dissertations and Theses @ UTEP, 2009. http://0-proquest.umi.com.lib.utep.edu/login?COPT=REJTPTU0YmImSU5UPTAmVkVSPTI=&clientId=2515.

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Postolski, Michal. "Discrete topology and geometry algorithms for quantitative human airway trees analysis based on computed tomography images." Phd thesis, Université Paris-Est, 2013. http://pastel.archives-ouvertes.fr/pastel-00977514.

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Computed tomography is a very useful technic which allow non-invasive diagnosis in many applications for example is used with success in industry and medicine. However, manual analysis of the interesting structures can be tedious and extremely time consuming, or even impossible due its complexity. Therefore in this thesis we study and develop discrete geometry and topology algorithms suitable for use in many practical applications, especially, in the problem of automatic quantitative analysis of the human airway trees based on computed tomography images. In the first part, we define basic noti
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Hawkins, Samuel Hunt. "Lung CT Radiomics| An Overview of Using Images as Data." Thesis, University of South Florida, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10633857.

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<p> Lung cancer is the leading cause of cancer-related death in the United States and worldwide. Early detection of lung cancer can help improve patient outcomes, and survival prediction can inform plans of treatment. By extracting quantitative features from computed tomography scans of lung cancer, predictive models can be built that can achieve both early detection and survival prediction. To build these predictive models, first a detected lung nodule is segmented, then image features are extracted, and finally a model can be built utilizing image features to make predictions. These predicti
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18

Thomas, Sarina [Verfasser], and Klaus H. [Akademischer Betreuer] Maier-Hein. "Automatic image analysis of C-arm Computed Tomography images for ankle joint surgeries / Sarina Thomas ; Betreuer: Klaus Hermann Maier-Hein." Heidelberg : Universitätsbibliothek Heidelberg, 2020. http://nbn-resolving.de/urn:nbn:de:bsz:16-heidok-283769.

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Thomas, Sarina [Verfasser], and Klaus Hermann [Akademischer Betreuer] Maier-Hein. "Automatic image analysis of C-arm Computed Tomography images for ankle joint surgeries / Sarina Thomas ; Betreuer: Klaus Hermann Maier-Hein." Heidelberg : Universitätsbibliothek Heidelberg, 2020. http://d-nb.info/1211820785/34.

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Lu, Jing [Verfasser]. "Advanced Methods for the Quantification of Trabecular Bone Structure and Density in Micro Computed Tomography Images / Jing Lu." Aachen : Shaker, 2011. http://d-nb.info/1071528580/34.

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Campbell, Matthew Stephen. "A Practical Method to Superimpose Sella Turcica in Serial CBCT Images." Master's thesis, Temple University Libraries, 2017. http://cdm16002.contentdm.oclc.org/cdm/ref/collection/p245801coll10/id/470228.

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Oral Biology<br>M.S.<br>Introduction: We argue, for studies of growth or treatment changes, superimposed CBCT images ought to be employed routinely. The location of 3D landmarks on curved structures, however, has been complex. In this study, a reliable method of CBCT superimposition was developed with the aid of AMIRA XImage® software. The specific focus was to develop a practical method for cranial base superimpositions at sella turcica in serial CBCT images. Subsequently, evaluations of the anterior curvature of hypophyseal fossa during growth were completed to confirm the stability. Compari
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Akasaka, Thai. "Detection of suspected brain infarctions on CT can be significantly improved with temporal subtraction images." Kyoto University, 2019. http://hdl.handle.net/2433/242382.

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Barnes, Anna Pauline. "Development and evaluation of quantitative methods of analysing single photon emission computed tomography blood flow images of the brain." Thesis, University of Glasgow, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300733.

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Liao, Hanqing. "Textural features for bladder cancer definition on CT images." Thesis, University of Edinburgh, 2013. http://hdl.handle.net/1842/7655.

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Genitourinary cancer refers to the presence of tumours in the genital or urinary organs such as bladder, kidney and prostate. In 2008 the worldwide incidence of bladder cancer was 382,600 with a mortality of 150,282. Radiotherapy is one of the main treatment choices for genitourinary cancer where accurate delineation of the gross tumour volume (GTV) on computed tomography (CT) images is crucial for the success of this treatment. Limited CT resolution and contrast in soft tissue organs make this difficult and has led to significant inter- and intra- clinical variability in defining the extent o
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Kubo, Takeshi. "Efficiency and reproducibility in pulmonary nodule detection in simulated dose reduction lung CT images." Kyoto University, 2019. http://hdl.handle.net/2433/243276.

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Kardell, Martin. "Automatic Segmentation of Tissues in CT Images of the Pelvic Region." Thesis, Linköpings universitet, Institutionen för medicinsk teknik, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-112540.

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In brachytherapy, radiation therapy is performed by placing the radiation source into or very close to the tumour. When calculating the absorbed dose, water is often used as the radiation transport and dose scoring medium for soft tissues and this leads to inaccuracies. The iterative reconstruction algorithm DIRA is under development at the Center for Medical Imaging Science and Visualization, Linköping University. DIRA uses dual-energy CT to decompose tissues into different doublets and triplets of base components for a better absorbed dose estimation. To accurately determine mass fractions o
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Sousa, Melo Saulo Leonardo. "The impact on diagnostic yield of the scan mode of cone beam CT images in artificial external root resorption." Thesis, University of Iowa, 2016. https://ir.uiowa.edu/etd/6292.

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Introduction: Root resorption is an undesired but frequent side effect of orthodontic treatment. Several studies have already aimed to evaluate the performance of CBCT on this topic. However, none have addressed the peculiarities of the most common daily orthodontic scenario. The aim of the study was to evaluate the influence of CBCT scans on the diagnosis of artificial external root resorption in the apical third of anterior teeth. Materials and methods: One hundred extracted human anterior teeth were randomly assigned to 2 uneven groups (51 as the control and 49 as the experimental group). A
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Queiroz, Polyane Mazucatto 1991. "Influência da ferramenta de redução de artefato metálico na qualidade de imagens de TCFC = Influence of metal artefact reduction tool in quality of CBCT images." [s.n.], 2015. http://repositorio.unicamp.br/jspui/handle/REPOSIP/290661.

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Orientador: Deborah Queiroz de Freitas França<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Odontologia de Piracicaba<br>Made available in DSpace on 2018-08-28T02:05:09Z (GMT). No. of bitstreams: 1 Queiroz_PolyaneMazucatto_M.pdf: 2757992 bytes, checksum: 06e73a8b08ccb2c9d71f5790996c28cb (MD5) Previous issue date: 2015<br>Resumo: Materiais de alta densidade física e alto número atômico quando presentes no objeto escaneado podem resultar em artefato nas imagens tomográficas. O artefato compromete a qualidade da imagem tomográfica, podendo inviabilizar o uso dessa
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Giordano, Mario [Verfasser]. "Study of pineal region venous system with three-dimensional post-processing of magnetic resonance and computed tomography images : anatomical and surgical aspects / Mario Giordano." Magdeburg : Universitätsbibliothek, 2016. http://d-nb.info/1129779866/34.

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Boydev, Christine. "Segmentation automatique des images de tomographie conique pour la radiothérapie de la prostate." Thesis, Valenciennes, 2015. http://www.theses.fr/2015VALE0030/document.

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Dans le contexte du traitement du cancer de la prostate, l’utilisation de la tomodensitométrie à faisceau conique (CBCT) pour la radiothérapie guidée par l’image, éventuellement adaptative, présente certaines difficultés en raison du faible contraste et du bruit important dans les images pelviennes. L’objectif principal de cette thèse est d’apporter des contributions méthodologiques pour le recalage automatique entre l’image scanner CT de référence et l’image CBCT acquise le jour du traitement. La première partie de nos contributions concerne le développement d’une stratégie de correction du p
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Alpuche, Aviles Jorge Edmundo. "The Development and Validation of a First Generation X-Ray Scatter Computed Tomography Algorithm for the Reconstruction of Electron Density Breast Images Using Monte Carlo Simulation." Journal of X-ray Science and Technology, IOS Press, 2011. http://hdl.handle.net/1993/4970.

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Breast CT is a promising modality whose inherent scatter could be used to reconstruct electron density (rho_e) images. This has led us to investigate the benefits of reconstructing linear attenuation coefficient (mu) and (rho_e) images of the breast. First generation CT provides a cost-effective and simple approach to reconstruct (rho_e) images in a laboratory but is limited by the anisotropic probability of scatter, attenuation, noise and contaminating scatter (coherent and multiple scatter). These issues were investigated using Monte Carlo (MC) simulations of a first generation breast scat
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Huang, Robin. "Statistical Shape Modelling and Segmentation of the Respiratory Airway." Thesis, The University of Sydney, 2016. http://hdl.handle.net/2123/16365.

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The human respiratory airway consists of the upper (nasal cavity, pharynx) and the lower (trachea, bronchi) respiratory tracts. Accurate segmentation of these two airway tracts can lead to better diagnosis and interpretation of airway-specific diseases, and lead to improvement in the localization of abnormal metabolic or pathological sites found within and/or surrounding the respiratory regions. Due to the complexity and the variability displayed in the anatomical structure of the upper respiratory airway along with the challenges in distinguishing the nasal cavity from non-respiratory regions
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Moores, Matthew T. "Bayesian computational methods for spatial analysis of images." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/84728/12/84728%28thesis%29.pdf.

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This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.
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Marchini, Monikelly do Carmo Nascimento 1986. "Influência do grau de rotação do aparelho e do crânio na espessura da cortical óssea em imagens de tomografia de feixe cônico : Evaluation of the influence of the unit and skull rotation on cortical bone thickness in cone beam computed tomography images." [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/290162.

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Orientador: Solange Maria de Almeida Bóscolo<br>Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Odontologia de Piracicaba<br>Made available in DSpace on 2018-08-24T18:23:38Z (GMT). No. of bitstreams: 1 Marchini_MonikellydoCarmoNascimento_D.pdf: 1392987 bytes, checksum: e5d4a72a80998af2c16e333f3dee6408 (MD5) Previous issue date: 2014<br>Resumo: A tomografia computadorizada de feixe cônico (TCFC) tem sido uma ferramenta de auxílio no diagnóstico, com várias aplicações clínicas. Devido ao aumento das diversas possibilidades de aquisição da imagem, há uma grande necessidade de
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Španěl, Michal. "Delaunay-based Vector Segmentation of Volumetric Medical Images." Doctoral thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2011. http://www.nusl.cz/ntk/nusl-261255.

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Image segmentation plays an important role in medical image analysis. Many segmentation algorithms exist. Most of them produce data which are more or less not suitable for further surface extraction and anatomical modeling of human tissues. In this thesis, a novel segmentation technique based on the 3D Delaunay triangulation is proposed. A modified variational tetrahedral meshing approach is used to adapt a tetrahedral mesh to the underlying CT volumetric data, so that image edges are well approximated in the mesh. In order to classify tetrahedra into regions/tissues whose characteristics are
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Mukkananchery, Abey. "Iterative Methods for the Reconstruction of Tomographic Images with Unconventional Source-detector Configurations." VCU Scholars Compass, 2005. http://scholarscompass.vcu.edu/etd/1244.

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X-ray computed tomography (CT) holds a critical role in current medical practice for the evaluation of patients, particularly in the emergency department and intensive care units. Expensive high resolution stationary scanners are available in radiology departments of most hospitals. In many situations however, a small, inexpensive, portable CT unit would be of significant value. Several mobile or miniature CT scanners are available, but none of these systems have the range, flexibility or overall physical characteristics of a truly portable device. The main challenge is the design of a geometr
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Gruselius, Hanna. "Generative Models and Feature Extraction on Patient Images and Structure Data in Radiation Therapy." Thesis, KTH, Matematisk statistik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-229407.

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This Master thesis focuses on generative models for medical patient data for radiation therapy. The objective with the project is to implement and investigate the characteristics of a Variational Autoencoder applied to this diverse and versatile data. The questions this thesis aims to answer are: (i) whether the VAE can capture salient features of medical image data, and (ii) if these features can be used to compare similarity between patients. Furthermore, (iii) if the VAE network can successfully reconstruct its input and lastly (iv) if the VAE can generate artificial data having a reasonabl
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Дзюра, Олена Юріївна. "Система обробки медичних 3D зображень для виявлення асиметрії". Bachelor's thesis, КПІ ім. Ігоря Сікорського, 2020. https://ela.kpi.ua/handle/123456789/35956.

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Обсяг пояснювальної записки 52 сторінки, міститься 24 ілюстрацій, 12 таблиць. Загалом опрацьовано 33 джерела. Актуальність роботи пов’язана із задачею удосконалення технології діагностичного виявлення дефектів (патологій) скелету в щелепо-лицевій хірургії та технології виготовлення відповідних штучних елементів для імплантації з використанням імітаційного комп’ютерного моделювання біологічних об’єктів. Мета: побудова комп’ютерної системи для автоматичного виявлення та візуалізації асиметрії 3-вимірних об’єктів шляхом їх порівняння зі своїм дзеркальним відображенням відносно оптимальним чино
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Wang, Zhihan. "Reconstruction des images médicales de tomodensitométrie spectrale par apprentissage profond." Electronic Thesis or Diss., Brest, 2024. http://www.theses.fr/2024BRES0124.

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La tomodensitométrie se concentre sur deux sujets clés : la réduction de la dose de radiation et l’imagerie multi-énergétique, qui sont interconnectés. La tomodensitométrie spectrale, une avancée émergente, capture des données sur plusieurs énergies de rayons X pour mieux distinguer les matériaux, minimisant le besoin de scans répétés et ainsi réduisant l’exposition globale aux radiations.Cependant, la réduction du nombre de photons dans chaque bin d’énergie rend les méthodes de reconstruction traditionnelles sensibles au bruit. Ainsi, l’apprentissage profond, qui a montré un potentiel considé
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Porto, Marcelo Arrais. "Uma técnica otimizada de clusterização para Segmentação de imagens de tc de tórax de alta-resolução." Universidade Federal de Santa Maria, 2016. http://repositorio.ufsm.br/handle/1/12169.

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Lung segmentation is a fundamental step in many image analysis applications for lung diseases and abnormalities in thoracic computed tomography (CT). However, due to the large variations in pathology that may be present in thoracic CT images, it is difficult to extract the lung regions accurately, especially when the lung parenchyma contains extensive lung diseases. A major insight to deal with this problem is the existence of new approaches to cope with quality and performance. This paper presents an optimized superpixel clustering approach for high-resolution chest CT segmentation. Th
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Niu, Pei. "Multi-energy image reconstruction in spectral photon-counting CT." Thesis, Lyon, 2020. http://www.theses.fr/2020LYSEI022.

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Le scanner CT spectral à comptage de photons (sCT) est apparu récemment comme une nouvelle technique d'imagerie présentant des avantages fondamentaux par rapport au scanner CT classique et au scanner CT à double énergie. Cependant, en raison du nombre réduit de photons dans chaque bande d'énergie du scanner sCT et des artéfacts divers, la reconstruction des images devient particulièrement difficile. Cette thèse se concentre sur la reconstruction d'images multi-énergie en sCT. Tout d'abord, nous proposons d'étudier la capacité du scanner sCT à réaliser simultanément une imagerie anatomique (aCT
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Velo, Alexandre França. "Análise da aplicação de diferentes algoritmos de reconstrução de imagens tomográficas de objetos industriais." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/85/85131/tde-08022019-142220/.

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Existe na indústria o interesse em utilizar as informações da tomografia computadorizada a fim de conhecer o interior (i) dos objetos industriais fabricados ou (ii) das máquinas e seus meios de produção. Nestes casos, a tomografia tem como finalidade (a) controlar a qualidade do produto final e (b) otimizar a produção, contribuindo na fase piloto dos projetos e na análise da qualidade dos meios sem interromper a produção. O contínuo controle de qualidade dos meios de produção é a chave mestra para garantir a qualidade e a competitividade dos produtos. O Centro de Tecnologia das Radiações (CTR)
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Hatvani, Janka. "Amélioration des images médicales à l'aide de techniques d'apprentissage profond et de factorisation tensorielle." Electronic Thesis or Diss., Toulouse 3, 2021. http://www.theses.fr/2021TOU30304.

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La résolution spatiale des images acquises par tomographie volumique à faisceau conique (CBCT) est limitée par la géométrie des capteurs, leur sensibilité, les mouvements du patient, les techniques de reconstruction d'images et la limitation de la dose de rayonnement. Le modèle de dégradation d'image considéré dans cette thèse consiste en un opérateur de ou avec la fonction d'étalement du système d'imagerie (PSF), un opérateur de décimation, et du bruit, qui relient les volumes CBCT à une image 3D super-résolue à estimer. Les méthodes proposées dans cette thèse (SISR - single image super-résol
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Morales, Pinzon Alfredo. "Lung segmentation and airway tree matching : application to aeration quantification in CT images of subjects with ARDS." Thesis, Lyon, 2016. http://www.theses.fr/2016LYSE1019/document.

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Le syndrome de détresse respiratoire aiguë (SDRA) présente un taux de mortalité élevé, près de 40%, dans des unités de soins intensifs. Il est défini comme un ensemble de manifestations cliniques, radiologiques et physiologiques qui traduisent une intense inflammation pulmonaire et une hyperperméabilité pulmonaire, correspondant aux différentes agressions aiguës du poumon. Le prise en charge des patients atteints du SDRA nécessite une ventilation assistée qui, en cas de mauvaise adaptation des paramètres de ventilation, notamment, pression et volume, peut aggraver l'état du patient. Le réglage
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Pacheco, Edward Florez. "Análise da dinâmica e quantificação metabólica de imagens de medicina nuclear na modalidade PET/CT." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/3/3142/tde-24062016-141858/.

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A presença da Medicina Nuclear como modalidade de obtenção de imagens médicas é um dos principais procedimentos utilizados hoje nos centros de saúde, tendo como grande vantagem a capacidade de analisar o comportamento metabólico do paciente, traduzindo-se em diagnósticos precoces. Entretanto, sabe-se que a quantificação em Medicina Nuclear é dificultada por diversos fatores, entre os quais estão a correção de atenuação, espalhamento, algoritmos de reconstrução e modelos assumidos. Neste contexto, o principal objetivo deste projeto foi melhorar a acurácia e a precisão na análise de imagens de P
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Hagvall, Hörnstedt Julia. "Synthesis of Thoracic Computer Tomography Images using Generative Adversarial Networks." Thesis, Linköpings universitet, Avdelningen för medicinsk teknik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-158280.

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The use of machine learning algorithms to enhance and facilitate medical diagnosis and analysis is a promising and an important area, which could improve the workload of clinicians’ substantially. In order for machine learning algorithms to learn a certain task, large amount of data needs to be available. Data sets for medical image analysis are rarely public due to restrictions concerning the sharing of patient data. The production of synthetic images could act as an anonymization tool to enable the distribution of medical images and facilitate the training of machine learning algorithms, whi
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Puerto, Lorena Paola Robayo. "Simulação Monte Carlo do processo de aquisição de imagens de um tomógrafo de dupla energia." Universidade de São Paulo, 2018. http://www.teses.usp.br/teses/disponiveis/43/43134/tde-16062018-092940/.

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A Tomografia Computadorizada de Energia Dupla (DECT em inglês) é um dos campos das imagens tomográficas que mais evoluiu nos últimos anos. O DECT usa dois espectros para irradiar pacientes e é capaz de diferenciar tecidos com base na sua composição elementar. Apesar de serem semelhantes aos dispositivos padrão de tomografia, para essa modalidade é necessário o desenvolvimento de ferramentas específicas que permitam o estudo de suas propriedades de imagem. O objetivo deste trabalho era construir um sistema simulado de Tomografia Computadorizada (TC) com a capacidade de produzir imagens semelhan
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Zossou, Vincent-Béni Sèna. "Détection du carcinome hépatocellulaire et des métastases hépatiques basée sur les images tomodensitométriques et l'apprentissage automatique." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASR034.

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Les médecins radiologues utilisent des séries d’images issues de la tomodensitométrie (TDM) abdominale pour examiner le foie et diagnostiquer les éventuelles pathologies. Cependant, ce processus est souvent long, complexe et sujet à des risques d’erreurs humaines. Les études des récentes années démontrent que l’intelligence artificielle (IA) a ouvert de nouvelles perspectives en imagerie médicale, permettant de détecter plus tôt les cancers du foie et d’optimiser l’ensemble du processus diagnostique. En Afrique, et particulièrement au Bénin, peu d’études ont été menées sur l’utilisation de ces
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Evans, Joshua. "Statistical image reconstruction for quantitative computed tomography." VCU Scholars Compass, 2011. http://scholarscompass.vcu.edu/etd/2557.

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Statistical iterative reconstruction (SIR) algorithms for x-ray computed tomography (CT) have the potential to reconstruct images with less noise and systematic error than the conventional filtered backprojection (FBP) algorithm. More accurate reconstruction algorithms are important for reducing imaging dose and for a wide range of quantitative CT applications. The work presented herein investigates some potential advantages of one such statistically motivated algorithm called Alternating Minimization (AM). A simulation study is used to compare the tradeoff between noise and resolution in i
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Hyun, Jung Kim. "Classification in thoracic computed tomography image data." Diss., Restricted to subscribing institutions, 2007. http://proquest.umi.com/pqdweb?did=1383469071&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.

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