Relevant bibliographies by topics / PET/CT image processing / Dissertations / Theses
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Dissertations / Theses on the topic 'PET/CT image processing'

Author: Grafiati
Published: 4 June 2021
Last updated: 14 February 2022

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1

Wang, Xue. "An Integrated Multi-modal Registration Technique for Medical Imaging." FIU Digital Commons, 2017. https://digitalcommons.fiu.edu/etd/3512.

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Registration of medical imaging is essential for aligning in time and space different modalities and hence consolidating their strengths for enhanced diagnosis and for the effective planning of treatment or therapeutic interventions. The primary objective of this study is to develop an integrated registration method that is effective for registering both brain and whole-body images. We seek in the proposed method to combine in one setting the excellent registration results that FMRIB Software Library (FSL) produces with brain images and the excellent results of Statistical Parametric Mapping (
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2

Desseroit, Marie-Charlotte. "Caractérisation et exploitation de l'hétérogénéité intra-tumorale des images multimodales TDM et TEP." Thesis, Brest, 2016. http://www.theses.fr/2016BRES0129/document.

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L’imagerie multi-modale Tomographie par émission de positons (TEP)/ Tomodensitométrie(TDM) est la modalité d’imagerie la plus utilisée pour le diagnostic et le suivi des patients en oncologie. Les images obtenues par cette méthode offrent une cartographie à la fois de la densité des tissus (modalité TDM) mais également une information sur l’activité métabolique des lésions tumorales (modalité TEP). L’analyse plus approfondie de ces images acquises en routine clinique a permis d’extraire des informations supplémentaires quant à la survie du patient ou à la réponse au(x) traitement(s). Toutes ce
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3

Eklund, Anders, Paul Dufort, Daniel Forsberg, and Stephen LaConte. "Medical Image Processing on the GPU : Past, Present and Future." Linköpings universitet, Medicinsk informatik, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-93673.

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Graphics processing units (GPUs) are used today in a wide range of applications, mainly because they can dramatically accelerate parallel computing, are affordable and energy efficient. In the field of medical imaging, GPUs are in some cases crucial for enabling practical use of computationally demanding algorithms. This review presents the past and present work on GPU accelerated medical image processing, and is meant to serve as an overview and introduction to existing GPU implementations. The review covers GPU acceleration of basic image processing operations (filtering, interpolation, hist
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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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5

Zheng, Yiran. "CT-PET Image Fusion and PET Image Segmentation for Radiation Therapy." Case Western Reserve University School of Graduate Studies / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=case1283542509.

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6

Åkesson, Lars. "Partial Volume Correction in PET/CT." Thesis, Stockholm University, Medical Radiation Physics (together with KI), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-8322.

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<p>In this thesis, a two-dimensional pixel-wise deconvolution method for partial volume correction (PVC) for combined Positron Emission Tomography and Computer Tomography (PET/CT) imaging has been developed. The method is based on Van Cittert's deconvolution algorithm and includes a noise reduction method based on adaptive smoothing and median filters. Furthermore, a technique to take into account the position dependent PET point spread function (PSF) and to reduce ringing artifacts is also described. The quantitative and qualitative performance of the proposed PVC algorithm was evaluated usin
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Baluwala, Habib. "Physically motivated registration of diagnostic CT and PET/CT of lung volumes." Thesis, University of Oxford, 2013. http://ora.ox.ac.uk/objects/uuid:797c00c0-1efa-43e2-8268-e3d09ced0e06.

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Lung cancer is a disease affecting millions of people every year and poses a serious threat to global public health. Accurate lung cancer staging is crucial to choose an appropriate treatment protocol and to determine prognosis, this requires the acquisition of contrast-enhanced diagnostic CT (d-CT) that is usually followed by a PET/CT scan. Information from both d-CT and PET scan is used by the clinician in the staging process; however, these images are not intrinsically aligned because they are acquired on different days and on different scanners. Establishing anatomical correspondence, i.e.
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8

D’Antò, Michela <1984&gt. "CT perfusion image processing: analysis of liver tumors." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2013. http://amsdottorato.unibo.it/5499/.

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Perfusion CT imaging of the liver has potential to improve evaluation of tumour angiogenesis. Quantitative parameters can be obtained applying mathematical models to Time Attenuation Curve (TAC). However, there are still some difficulties for an accurate quantification of perfusion parameters due, for example, to algorithms employed, to mathematical model, to patient’s weight and cardiac output and to the acquisition system. In this thesis, new parameters and alternative methodologies about liver perfusion CT are presented in order to investigate the cause of variability of this technique.
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9

Kotasidis, Fotis. "Spatiotemporal image reconstruction with resolution recovery for dynamic PET/CT in oncology." Thesis, University of Manchester, 2011. https://www.research.manchester.ac.uk/portal/en/theses/spatiotemporal-image-reconstruction-with-resolution-recovery-for-dynamic-petct-in-oncology(d3f936ed-f917-42a2-8842-e7f50b244035).html.

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Positron emission tomography (PET) is a powerful and highly specialised imaging modality that has the inherent ability to detect and quantify changes in the bio-distribution of an intravenously administered radio-labelled tracer, through dynamic image acquisition of the system under study. By modelling the temporal distribution of the tracer, parameters of interest regarding specific biological processes can be derived. Traditionally parameter estimation is done by first reconstructing a set of dynamic images independently, followed by kinetic modelling, leading to parameters of reduced accura
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10

Lee, Ki Sung. "Pragmatic image reconstruction for high resolution PET scanners /." Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/5967.

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11

Lau, Yu-ching, and 劉禹政. "Impact of time-of-flight technology on PET/CT image quality and SUV quantitation." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B49617527.

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Time-of-flight technology (TOF) is at the leading edge of advancements in PET/CT imaging, and is made possible due to the availability of new scanner design, scintillating materials and fast computers. The location of annihilation is estimated according to the time difference between scintillation events produced by two 511KeV gamma photons travelling in opposite directions. The additional information is incorporated into image reconstruction to suppress noise propagation and increase signal-to-noise ratio. As shown in previous studies, these properties can be translated in to clinical usage
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12

Lilja, Johan. "[18F]Flutemetamol PET image processing, visualization and quantification targeting clinical routine." Doctoral thesis, Uppsala universitet, Radiologi, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-317688.

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Alzheimer’s disease (AD) is the leading cause of dementia and is alone responsible for 60-70% of all cases of dementia. Though sharing clinical symptoms with other types of dementia, the hallmarks of AD are the abundance of extracellular depositions of β-amyloid (Aβ) plaques, intracellular neurofibrillary tangles of hyper phosphorylated tau proteins and synaptic depletion. The onset of the physiological hallmarks may precede clinical symptoms with a decade or more, and once clinical symptoms occur it may be difficult to separate AD from other types of dementia based on clinical symptoms alone.
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13

Klintström, Eva. "Image Analysis for Trabecular Bone Properties on Cone-Beam CT Data." Doctoral thesis, Linköpings universitet, Centrum för medicinsk bildvetenskap och visualisering, CMIV, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-142066.

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Trabecular bone structure as well as bone mineral density (BMD) have impact on the biomechanical competence of bone. In osteoporosis-related fractures, there have been shown to exist disconnections in the trabecular network as well as low bone mineral density. Imaging of bone parameters is therefore of importance in detecting osteoporosis. One available imaging device is cone-beam computed tomography (CBCT). This device is often used in pre-operative imaging of dental implants, for which the trabecular network also has great importance. Fourteen or 15 trabecular bone specimens from the radius
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Mårtensson, Fredrik, and Erik Westberg. "Prioritization of Informative Regions in PET Scans for Classification of Alzheimer's Disease." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-45370.

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Alzheimer’s Disease (AD) is a widespread neurodegenerative disease. The disease causes brain atrophy, resulting in memory loss, decreased cognitive ability, and eventually death. There is currently no cure for the disease, but treatment may delay the onset. Therefore, it is crucial to detect the disease at an early stage. Medical imaging techniques, such as Positron Emission Tomography (PET), are heavily applied for this task. In recent years, machine learning approaches have shown success in identifying AD from such images. The thesis presents a pipeline approach to detect, extract and evalua
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Oliver, Jasmine Alexandria. "Increasing 18F-FDG PET/CT Capabilities in Radiotherapy for Lung and Esophageal Cancer via Image Feature Analysis." Scholar Commons, 2016. http://scholarcommons.usf.edu/etd/6123.

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Positron Emission Tomography (PET) is an imaging modality that has become increasingly beneficial in Radiotherapy by improving treatment planning (1). PET reveals tumor volumes that are not well visualized on computed tomography CT or MRI, recognizes metastatic disease, and assesses radiotherapy treatment (1). It also reveals areas of the tumor that are more radiosensitive allowing for dose painting - a non-homogenous dose treatment across the tumor (1). However, PET is not without limitations. The quantitative unit of PET images, the Standardized Uptake Value (SUV), is affected by many factor
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16

Dong, Xue. "Novel methods for scatter correction and dual energy imaging in cone-beam CT." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51903.

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Excessive imaging doses from repeated scans and poor image quality mainly due to scatter contamination are the two bottlenecks of cone-beam CT (CBCT) imaging. This study investigates a method that combines measurement-based scatter correction and a compressed sensing (CS)-based iterative reconstruction algorithm to generate scatter-free images from low-dose data. Scatter distribution is estimated by interpolating/extrapolating measured scatter samples inside blocked areas. CS-based iterative reconstruction is finally carried out on the under-sampled data to obtain scatter-free and low-dose CBC
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17

ZHAO, HANG. "Segmentation and synthesis of pelvic region CT images via neural networks trained on XCAT phantom data." Thesis, Linköpings universitet, Datorseende, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-178209.

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Deep learning methods for medical image segmentation are hindered by the lack of training data. This thesis aims to develop a method that overcomes this problem. Basic U-net trained on XCAT phantom data was tested first. The segmentation results were unsatisfactory even when artificial quantum noise was added. As a workaround, CycleGAN was used to add tissue textures to the XCAT phantom images by analyzing patient CT images. The generated images were used totrain the network. The textures introduced by CycleGAN improved the segmentation, but some errors remained. Basic U-net was replaced with
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18

Doré, Sylvie. "Experimental identification of X-ray CT system characteristics for an improved understanding of image processing." Thesis, McGill University, 1992. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=39338.

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The first goal of this study was to develop experimental tools to estimate the blur and noise characteristics of X-ray CT systems. We evaluated the noise power spectrum (NPS) using the averaged periodogram technique. As predicted by theory, varying the image reconstruction filter produced a shift in the frequency content while slice thickness only affected the amplitude of the noise.<br>In order to quantify the blur, we developed and evaluated two non-linear parametric models of the point spread function (PSF): the Gaussian and damped cosine models. We fitted these models to images of spatiall
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Sharif, Mhd Saeed. "An artificial intelligent system for oncological volumetric medical PET classification." Thesis, Brunel University, 2013. http://bura.brunel.ac.uk/handle/2438/13095.

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Positron emission tomography (PET) imaging is an emerging medical imaging modality. Due to its high sensitivity and ability to model physiological function, it is effective in identifying active regions that may be associated with different types of tumour. Increasing numbers of patient scans have led to an urgent need for the development of new efficient data analysis system to aid clinicians in the diagnosis of disease and save decent amount of the processing time, as well as the automatic detection of small lesions. In this research, an automated intelligent system for oncological PET volum
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Björnfot, Magnus. "Extension of DIRA (Dual-Energy Iterative Algorithm) to 3D Helical CT." Thesis, Linköpings universitet, Datorseende, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-138595.

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There is a need for quantitative CT data in radiation therapy. Currently there are only few algorithms that address this issue, for instance the commercial DirectDensity algorithm. In scientific literature, an example of such an algorithm is DIRA. DIRA is an iterative model-based reconstruction method for dual-energy CT whose goal is to determine the material composition of the patient from accurate linear attenuation coefficients. It has been implemented in a two dimensional geometry, i.e., it could process axial scans only.  There was a need to extend DIRA so that it could process projection
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21

Gao, Zhiyun. "Novel multi-scale topo-morphologic approaches to pulmonary medical image processing." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/805.

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The overall aim of my PhD research work is to design, develop, and evaluate a new practical environment to generate separated representations of arterial and venous trees in non-contrast pulmonary CT imaging of human subjects and to extract quantitative measures at different tree-levels. Artery/vein (A/V) separation is of substantial importance contributing to our understanding of pulmonary structure and function, and immediate clinical applications exist, e.g., for assessment of pulmonary emboli. Separated A/V trees may also significantly boost performance of airway segmentation methods for h
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Onoue, Koji. "CT temporal subtraction improves early detection of bone metastases compared to SPECT." Kyoto University, 2020. http://hdl.handle.net/2433/253152.

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Boelen, E. "Innovations in medical image processing for the design of custom medical devices and implants." Journal for New Generation Sciences, Vol 8, Issue 2: Central University of Technology, Free State, Bloemfontein, 2010. http://hdl.handle.net/11462/557.

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Published Article<br>In this article we will describe the use of 3D medical image information of individual patients as well as selected patient populations, combined with CAE tools and processes, in the rapid product development of custom and standard implantable devices. The combination of medical image information with CAE methods such as CAD, RP, FEA and CFD, allows the engineer to develop implantable devices faster and better, with optimized designs tailored to the anthropometry of the targeted patient (population), using virtual instead of mechanical prototype testing. Case studies will
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Wang, Chengjia. "Development of registration methods for cardiovascular anatomy and function using advanced 3T MRI, 320-slice CT and PET imaging." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/22918.

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Different medical imaging modalities provide complementary anatomical and functional information. One increasingly important use of such information is in the clinical management of cardiovascular disease. Multi-modality data is helping improve diagnosis accuracy, and individualize treatment. The Clinical Research Imaging Centre at the University of Edinburgh, has been involved in a number of cardiovascular clinical trials using longitudinal computed tomography (CT) and multi-parametric magnetic resonance (MR) imaging. The critical image processing technique that combines the information from
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Wang, Qian. "Processing and exploration of CT images for the assessment of aortic valve bioprostheses." Phd thesis, Université Rennes 1, 2013. http://tel.archives-ouvertes.fr/tel-00925743.

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The aim of the study was to assess the feasibility of CT based 3D analysis of degenerated aortic bioprostheses to make easier their morphological assessment. This could be helpful during regular follow-up and for case selection, improved planning and mapping of valve-in-valve procedure. The challenge was represented by leaflets enhancement because of highly noised CT images. Contrast-enhanced ECG-gated CT scan was performed in patients with degenerated aortic bioprostheses before reoperation (in-vivo images). Different methods for noise reduction were tested and proposed. 3D reconstruction of
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Cutipa, Arapa Efraina Gladys. "Aplicação da codificação ROI e WT para compressão de imagens DICOM-CT." [s.n.], 2012. http://repositorio.unicamp.br/jspui/handle/REPOSIP/260054.

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Orientador: Yuzo Iano<br>Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação<br>Made available in DSpace on 2018-08-20T02:17:41Z (GMT). No. of bitstreams: 1 CutipaArapa_EfrainaGladys_M.pdf: 5028658 bytes, checksum: 07c8aaabf3096b4e5cd565e0f12f6fe6 (MD5) Previous issue date: 2012<br>Resumo: O armazenamento e a transmissão de grande quantidade de imagens médicas constituem um campo ativo de pesquisa. Dispositivos de imagem geram muitos dados por paciente. Além disso, deve-se prover armazenamento de longo prazo bem como uma transmissão ef
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Lindahl, Jens. "Correlation between PET/MRI image features andpathological subtypes for localized prostate cancer." Thesis, Umeå universitet, Institutionen för fysik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184885.

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Prostate cancer is the most common cancer in Sweden. Patients with the condition have a good prognosis in general and most cases can be treated. Localized prostate cancer is primarily treated via surgery or radiation therapy and is diagnosed with the help of different imaging modalities, such as magnetic resonance imaging, MRI, and positron emission tomography, PET. The diagnosis is confirmed and the aggressiveness of the cancer is determined through biopsies. Samples from a small part of the prostate are extracted and then examined. This could mean that parts of higher aggressiveness may be m
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Sunnegårdh, Johan. "Combining analytical and iterative reconstruction in helical cone-beam CT." Licentiate thesis, Computer Vision, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8286.

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<p>Contemporary algorithms employed for reconstruction of 3D volumes from helical cone beam projections are so called non-exact algorithms. This means that the reconstructed volumes contain artifacts irrespective of the detector resolution and number of projection angles employed in the process. In this thesis, three iterative schemes for suppression of these so called cone artifacts are investigated.</p><p>The first scheme, iterative weighted filtered backprojection (IWFBP), is based on iterative application of a non-exact algorithm. For this method, artifact reduction, as well as spatial res
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Walker, Matthew David. "Quantitative dynamic 3D PET scanning of the body and brain using LSO tomographs." Thesis, University of Manchester, 2009. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:78135.

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Wenan, Chen. "Automated Measurement of Midline Shift in Brain CT Images and its Application in Computer-Aided Medical Decision Making." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/121.

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The severity of traumatic brain injury (TBI) is known to be characterized by the shift of the middle line in brain as the ventricular system often changes in size and position, depending on the location of the original injury. In this thesis, the focus is given to processing of the CT (Computer Tomography) brain images to automatically calculate midline shift in pathological cases and use it to predict Intracranial Pressure (ICP). The midline shift measurement can be divided into three steps. First the ideal midline of the brain, i.e., the midline before injury, is found via a hierarchical sea
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Meilinger, Manuel [Verfasser]. "Metal artifact reduction and image processing of cone-beam computed tomography data for mobile C-arm CT devices / Manuel Meilinger." Regensburg : Univ.-Verl. Regensburg, 2011. http://d-nb.info/1012922480/34.

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Cabrera, Gil Blanca. "Deep Learning Based Deformable Image Registration of Pelvic Images." Thesis, KTH, Skolan för kemi, bioteknologi och hälsa (CBH), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279155.

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Deformable image registration is usually performed manually by clinicians,which is time-consuming and costly, or using optimization-based algorithms, which are not always optimal for registering images of different modalities. In this work, a deep learning-based method for MR-CT deformable image registration is presented. In the first place, a neural network is optimized to register CT pelvic image pairs. Later, the model is trained on MR-CT image pairs to register CT images to match its MR counterpart. To solve the unavailability of ground truth data problem, two approaches were used. For the
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Jacome, Victor Roland. "Evaluation of dose and image quality parameters for cone-beam CT localization protocols in radiation therapy." Oklahoma City : [s.n.], 2009.

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Lázňovský, Jakub. "Analýza dýchacích cest předčasně narozených dětí na základě MRI a CT dat." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2020. http://www.nusl.cz/ntk/nusl-413140.

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Předkládaná Diplomová práce se zabývá analýzou a tvorbou modelů dýchacích cest předčasně narozených dětí. Nejprve je položen teoretický základ v oblasti vývoje dýchacího ústrojí a tvorby modelů dýchacích cest. Poté jsou představeny využité zobrazovací modality a popsány metody pro práci s obrazovými daty. Praktická část práce se zabývá vytvořením modelů dýchacích cest tří novorozenců. Všechny tyto modely jsou vytvořeny na základě klinických CT a MRI dat novorozenců narozených ve 30. týdnu gestačního věku. U těchto vytvořených modelů jsou dále analyzovány vybrané parametry související s anatomi
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Hedman, Karolina. "Differences in tumor volume for treated glioblastoma patients examined with 18F-fluorothymidine PET and contrast-enhanced MRI." Thesis, Umeå universitet, Institutionen för fysik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-173693.

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Background: Glioblastoma (GBM) is the most common and malignant primary brain tumor. It is a rapidly progressing tumor that infiltrates the adjacent healthy brain tissue and is difficult to treat. Despite modern treatment including surgical resection followed by radiochemotherapy and adjuvant chemotherapy, the outcome remains poor. The median overall survival is 10-12 months. Neuroimaging is the most important diagnostic tool in the assessment of GBMs and the current imaging standard is contrast-enhanced magnetic resonance imaging (MRI). Positron emission tomography (PET) has been recommended
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Park, Seonyeong. "Respiratory Prediction and Image Quality Improvement of 4D Cone Beam CT and MRI for Lung Tumor Treatments." VCU Scholars Compass, 2017. http://scholarscompass.vcu.edu/etd/5046.

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Identification of accurate tumor location and shape is highly important in lung cancer radiotherapy, to improve the treatment quality by reducing dose delivery errors. Because a lung tumor moves with the patient's respiration, breathing motion should be correctly analyzed and predicted during the treatment for prevention of tumor miss or undesirable treatment toxicity. Besides, in Image-Guided Radiation Therapy (IGRT), the tumor motion causes difficulties not only in delivering accurate dose, but also in assuring superior quality of imaging techniques such as four-dimensional (4D) Cone Beam Co
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Malusek, Alexandr. "Calculation of scatter in cone beam CT : Steps towards a virtual tomograph." Doctoral thesis, Linköping : Department of Medical and Health Sciences, Linköping University, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-11275.

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Lekan, Michael D. "Impact of Bilateral Filter Parameters on Medical Image Noise Reduction and Edge Preservation." University of Toledo Health Science Campus / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=mco1263404507.

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Badic, Bogdan. "Caractérisation multiparamétrique des cancers colorectaux." Thesis, Brest, 2018. http://www.theses.fr/2018BRES0070/document.

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L’imagerie est un outil pour réaliser le diagnostic, le bilan d’extension et le suivi thérapeutique de la grande majorité des tumeurs. La tomodensitométrie (TDM) est la méthode la plus utilisée et les images obtenues fournissent une cartographie tumorale fondée sur la densité des tissus. L’analyse plus approfondie de ces images acquises en routine clinique a permis d’extraire des informations supplémentaires quant à la survie du patient ou à la réponse au(x) traitement(s). Toutes ces nouvelles données permettent de décrire le phénotype d’une lésion de façon non invasive et sont regroupées sous
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Levi, Jacob. "Automated Beam Hardening Correction for Myocardial Perfusion Imaging using Computed Tomography." Case Western Reserve University School of Graduate Studies / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=case1553868329519413.

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Lopez-Hernandez, Juan. "Imagerie Cardiaque Multimodalités 2D et 3D :application à la Coronarographie/Tomoscintigraphie/TEP-CT." Phd thesis, Institut National Polytechnique de Lorraine - INPL, 2006. http://tel.archives-ouvertes.fr/tel-00118991.

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La coronarographie et la tomoscintigraphie (SPECT, de l'anglais "Single Photon Emission Computed<br />Tomography") sont deux techniques d'imagerie utilisées couramment pour diagnostiquer les maladies<br />cardiovasculaires. La première modalité est constituée de séquences d'images à rayon X visualisant chacune,<br />dans un même plan, les artères coronaires situées sur la face avant et la face arrière du coeur. Les images à<br />rayons X fournissent des informations anatomiques liées à l'arbre artériel et mettent en évidence d'éventuels<br />rétrécissements des artères (sténoses). La modalité
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42

Trávníčková, Kateřina. "Interaktivní segmentace 3D CT dat s využitím hlubokého učení." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2020. http://www.nusl.cz/ntk/nusl-432864.

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This thesis deals with CT data segmentation using convolutional neural nets and describes the problem of training with limited training sets. User interaction is suggested as means of improving segmentation quality for the models trained on small training sets and the possibility of using transfer learning is also considered. All of the chosen methods help improve the segmentation quality in comparison with the baseline method, which is the use of automatic data specific segmentation model. The segmentation has improved by tens of percents in Dice score when trained with very small datasets. T
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Na, Hana. "A study on detection of risk factors of a toddler's fall injuries using visual dynamic motion cues." Thesis, Brunel University, 2009. http://bura.brunel.ac.uk/handle/2438/3214.

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The research in this thesis is intended to aid caregivers’ supervision of toddlers to prevent accidental injuries, especially injuries due to falls in the home environment. There have been very few attempts to develop an automatic system to tackle young children’s accidents despite the fact that they are particularly vulnerable to home accidents and a caregiver cannot give continuous supervision. Vision-based analysis methods have been developed to recognise toddlers’ fall risk factors related to changes in their behaviour or environment. First of all, suggestions to prevent fall events of you
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Melki, Imen. "Towards an automated framework for coronary lesions detection and quantification in cardiac CT angiography." Thesis, Paris Est, 2015. http://www.theses.fr/2015PESC1022/document.

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Les maladies coronariennes constituent l'ensemble des troubles affectant les artères coronaires. Elles sont la première cause mondiale de mortalité. Par conséquent, la détection précoce de ces maladies en utilisant des techniques peu invasives fournit un meilleur résultat thérapeutique, et permet de réduire les coûts et les risques liés à une approche interventionniste. Des études récentes ont montré que la tomodensitométrie peut être utilisée comme une alternative non invasive et fiable pour localiser et quantifier ces lésions. Cependant, l'analyse de ces examens, basée sur l'inspection des s
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Niehues, Stefan Markus. "Stellenwert der Bildfusion von Positronenemissionstomographie und Computertomographie bei onkologischen Erkrankungen des Pankreas." Doctoral thesis, [S.l.] : [s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=964361043.

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Pattiam, Giriprakash Pavithran. "Systemic Identification of Radiomic Features Resilient to Batch Effects and Acquisition Variations for Diagnosis of Active Crohn's Disease on CT Enterography." Cleveland State University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=csu1629542175523398.

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Näsmark, Torbjörn. "Dual Energy CT as a Foundation for Proton Therapy Treatmen Planning - A pilot study." Thesis, Umeå universitet, Institutionen för fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160583.

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The treatment plan for radiation therapy with protons is based on images from a computed tomography (CT) scanner. This is problematic since the photons in the x-ray beam from the CT scanner and the protons are affected differently by the tissue in the patient, which introduce an uncertainty in the track length of the protons. The hypothesis of this study is that a new generation of CT scanners (DECT), with the capacity to simultaneously scan the patient with two photon spectra of different mean energy, will improve the tissue characterisation and which in turn reduce the uncertainty in the tra
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48

Tesařová, Markéta. "Využití průmyslové rentgenové počítačové mikrotomografie ve vývojové biologii." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2018. http://www.nusl.cz/ntk/nusl-382253.

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Rentgenová počítačová mikrotomografie (CT) je metoda pro trojrozměrné (3D) zobrazování vnitřní struktury objektů. Laboratoř rentgenové počítačové mikro a nanotomografie na CEITEC VUT (Středoevropský technologický institut, Vysoké učení technické v Brně) se zaměřuje zejména na nedestruktivní analýzu v průmyslovém odvětví. Ukázalo se ale, že tato metoda nachází široké uplatnění i v dalších vědeckých oblastech včetně vývojové biologie. Tato práce poskytuje propojení mezi materiálovými a živými vědami. Kompletní proces vedoucí k vytvoření 3D modelu různých anatomických struktur je detailně popsán.
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Lidayová, Kristína. "Fast Methods for Vascular Segmentation Based on Approximate Skeleton Detection." Doctoral thesis, Uppsala universitet, Avdelningen för visuell information och interaktion, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-318796.

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Modern medical imaging techniques have revolutionized health care over the last decades, providing clinicians with high-resolution 3D images of the inside of the patient's body without the need for invasive procedures. Detailed images of the vascular anatomy can be captured by angiography, providing a valuable source of information when deciding whether a vascular intervention is needed, for planning treatment, and for analyzing the success of therapy. However, increasing level of detail in the images, together with a wide availability of imaging devices, lead to an urgent need for automated t
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Chen, Mitchell. "Computer-assisted volumetric tumour assessment for the evaluation of patient response in malignant pleural mesothelioma." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:44c0aef6-5f1b-4777-91d8-5bc663df2503.

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Malignant pleural mesothelioma (MPM) is a form of aggressive tumour that is almost always associated with prior exposure to asbestos. Currently responsible for over 47,000 deaths worldwide each year and rising, it poses a serious threat to global public health. Many clinical studies of MPM, including its diagnosis, prognostic planning, and the evaluation of a treatment, necessitate the accurate quantification of tumours based on medical image scans, primarily computed tomography (CT). Currently, clinical best practice requires application of the MPM-adapted Response Evaluation Criteria in Soli
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