Concerns arise in radiation therapy for head and neck cancers when dental prostheses are involved. These prostheses are high-density materials that induce image artifacts in computed tomography (CT) scans used for dose calculation. Two approaches are utilized in mitigating the impact of these artifacts on the accuracy of dose calculation. First, metal artifact reduction (MAR) algorithms or dual-energy CT scans are used to recover image quality. Second, a planning protocol is adopted whereby residual artifacts are manually contoured and assigned appropriate densities. This study evaluated the current planning process using a holistic approach. In this work, an axial section of a head phantom containing dental implants at the level of the oral cavity was constructed and scanned using various protocols on two different commercial scanners; Philips and Siemens, to assess the appearance of artifacts. An MVCT image set was merged with the corresponding kVCT image to improve visualization of the dental implants for use in density overrides. Three ion chamber measurement points in the simulated mouth facilitated the determination of measured dose which was compared to calculated dose at various single beam irradiation geometries. The influence of density override values on agreement between calculation and measurement was investigated for each geometry and imaging modality. Percent error was computed, and initial results compared to results manipulated by use of; a CT density table (Head); density overrides of walls and wax; and density overrides of walls, wax, and effective density of saturation regions. The study established that normal tissue doses are not significantly affected by metal artifact reduction (MAR) algorithms, and improvements in dose calculation compared to uncorrected CT images are small. Furthermore, the inclusion of a MVCT image set improved implant visualization reducing the treatment planning time while providing more information. Evidence led to the deduction that manual overrides of effective density for clipped OMAR CT pixels reduce dose calculation errors. When the phantom was configured with amalgam and Co-Cr-Mo alloy dental implants the effective density of these implants was found to be 4.5 g/cm3. When the phantom was configured with implants containing amalgam and gold, the effective density of amalgam in the presence of gold was 5.5 g/cm3 while gold had an effective density of 6.5 g/cm3. The median and maximum range of errors for the uncorrected images were ± 0.6 % and 7.4% respectively for the phantom configured with amalgam and Co-Cr-Mo (tray one) and ± 0.5 % and 18.1 % respectively for the phantom containing amalgam and gold (tray two). The median and maximum range of errors for the corrected images after applying overrides of effective densities were ± 0.5 % and 4.7% respectively for tray one and ± 0.3 % and 7.7 % respectively for tray two. In conclusion, introduction of density overrides of walls, wax and effective density of high-density materials can reduce the errors induced by metal artifacts and improve the accuracy of dose calculations in treatment planning systems to deliver the relevant dose to a target organ. / Thesis / Master of Science (MSc)

No description available.

The research related to designing portable monitoring devices for physiological signals has been at its peak in the last decade or two. One of the main obstacles in building such devices is the effect of the subject's movements on the quality of the signal. There have been numerous studies addressing the problem of removing motion artifact from the electrocardiogram (ECG) and photoplethysmography (PPG) signals in the past few years. However, no such study exists for the Impedance Plethysmography (IP) signal. The IP signal can be used to monitor respiration in mobile devices. However, it is very susceptible to motion artifact. The main aim of this dissertation is to develop adaptive and non-adaptive filtering algorithms to address the problem of motion artifact reduction from the IP signal.

Submitted by Jean Medeiros (jeanletras@uepb.edu.br) on 2017-10-23T13:03:47Z No. of bitstreams: 1 PDF - José Alberto Souza Paulino.pdf: 32306126 bytes, checksum: d8a3a4c1c537e36b743590e029308f8c (MD5) / Approved for entry into archive by Secta BC (secta.csu.bc@uepb.edu.br) on 2017-10-26T16:55:17Z (GMT) No. of bitstreams: 1 PDF - José Alberto Souza Paulino.pdf: 32306126 bytes, checksum: d8a3a4c1c537e36b743590e029308f8c (MD5) / Made available in DSpace on 2017-10-26T16:55:17Z (GMT). No. of bitstreams: 1 PDF - José Alberto Souza Paulino.pdf: 32306126 bytes, checksum: d8a3a4c1c537e36b743590e029308f8c (MD5) Previous issue date: 2017-05-08 / This research proposes to evaluate and implement a solution for metal artifact reduc- tion in computed tomography, this one aiming to meet a demand from the prototyping laboratory of the Núcleo de Tecnologias Estratégicas em Saúde (Nutes) da Univer- sidade Estadual da Paraíba, where impressions of biomodels are made for surgical planning. The CT affected by metal artifacts need to be corrected prior to the printing process, this manual intervention implies excessive delay for delivery of the biomodels. The development of the proposed solution is based on the sinogram correction method which according to Mouton et al (2013) and Gjesteby (2016) is the most utilized method for reducing metal artifacts and makes uses of linear interpolation to correction the cor- rupted data. In order to validate the preference for linear interpolation in the state of the art, others interpolative techniques were implemented and evaluated; Fist through simulations and then by a form for qualitative evaluation, upon which statistical tests were applied. The results obtained confirm the use of interpolation as the best option for the reconstruction of data corrupted by metallic artifacts. / Esta pesquisa se propõe a avaliar e implementar uma solução para redução de artefatos metálicos em tomografias computadorizadas, solução esta que visa atender uma demanda do laboratório de prototipagem do Núcleo de Tecnologias Estratégicas em Saúde (Nutes) da Universidade Estadual da Paraíba, onde são realizadas impressões de biomodelos para planejamentos cirúrgicos. As tomografias afetadas por artefatos metálicos necessitam de correção antes do processo de impressão, esta intervenção realizada de forma manual implica em demora excessiva para entrega dos biomodelos. O desenvolvimento da solução proposta baseia-se no método de correção de sinograma que, de acordo com Mouton et al (2013) e Gjesteby (2016), é o método mais difundido para redução de artefatos metálicos e faz uso da técnica de interpolação linear para correção dos dados corrompidos. Objetivando validar a preferência pelo uso da interpolação linear no estado da arte, foram implementadas outras técnicas interpolativas as quais foram submetidas a avaliação; Primeiro por meio de simulações e depois via fomulário para avaliação qualitativa, na qual foram aplicados testes estatísticos. Os resultados obtidos ratificam o uso da interpolação linear como melhor opção para reconstrução de dados corrompidos pelos artefatos metálicos.

No description available.

Magnetic Resonance Imaging (MRI) is an important diagnostic tool for imaging soft tissue without the use of ionizing radiation. Moreover, through advanced signal processing, MRI can provide more than just anatomical information, such as estimates of tissue-specific physical properties. Signal processing lies at the very core of the MRI process, which involves input design, information encoding, image reconstruction, and advanced filtering. Based on signal modeling and estimation, it is possible to further improve the images, reduce artifacts, mitigate noise, and obtain quantitative tissue information. In quantitative MRI, different physical quantities are estimated from a set of collected images. The optimization problems solved are typically nonlinear, and require intelligent and application-specific algorithms to avoid suboptimal local minima. This thesis presents several methods for efficiently solving different parameter estimation problems in MRI, such as multi-component T2 relaxometry, temporal phase correction of complex-valued data, and minimizing banding artifacts due to field inhomogeneity. The performance of the proposed algorithms is evaluated using both simulation and in-vivo data. The results show improvements over previous approaches, while maintaining a relatively low computational complexity. Using new and improved estimation methods enables better tissue characterization and diagnosis. Furthermore, a sequence design problem is treated, where the radio-frequency excitation is optimized to minimize image artifacts when using amplifiers of limited quality. In turn, obtaining higher fidelity images enables improved diagnosis, and can increase the estimation accuracy in quantitative MRI.

With the advance of the LCD technology, video quality is becoming increasingly important. In this thesis, we develop hardware-friendly low-complexity enhancement algorithms. Video quality enhancement methods can be classified into two main categories. Single frame methods are the first category. These methods have generally low computational complexity. Multi-frame methods combine information from more than one frame and require the motion information of objects in the scene to do so. We first concentrate on the contrast-enhancement problem by using both global (frame-wise) and local information derived from the image. We use the image histogram and present a regularization-based histogram modification method to avoid problems that are often created by histogram equalization. Next, we design a compression artifact reduction algorithm that reduces ringing artifacts, which is disturbing especially on large displays. Furthermore, to remove the blurriness in the original video we present a non-iterative diffusion-based sharpening algorithm, which enhances edges in a ringing-aware fashion. The diffusion-based technique works on gradient approximations in a neighborhood individually. This gives more freedom compared to modulating the high-pass filter output that is used to sharpen the edges. Motion estimation enables applications such as motion-compensated noise reduction, frame-rate conversion, de-interlacing, compression, and super-resolution. Motion estimation is an ill-posed problem and therefore requires the use of prior knowledge on motion of objects. Objects have inertia and are usually larger then pixels or a block of pixels in size, which creates spatio-temporal correlation. We design a method that uses temporal redundancy to improve motion-vector search by choosing bias vectors from the previous frame and adaptively penalizes deviations from the bias vectors. This increases the robustness of the motion-vector search. The spatial correlation is more reliable because temporal correlation is difficult to use when the objects move fast or accelerate in time, or have small sizes. Spatial smoothness is not valid across motion boundaries. We investigate using energy minimization for motion estimation and incorporate the spatial smoothness prior into the energy. By formulating the energy minimization iterations for each motion vector as the primal problem, we show that the dual problem is motion segmentation for that specific motion vector.

Cette thèse est constituée de deux principaux axes de recherche portant sur l'imagerie dentaire par la tomographie à rayons X : le développement de nouvelles méthodes itératives de reconstruction tomographique afin de réduire les artefacts métalliques et la réduction de la dose délivrée au patient. Afin de réduire les artefacts métalliques, nous prendrons en compte le durcissement du spectre des faisceaux de rayons X et le rayonnement diffusé. La réduction de la dose est abordée dans cette thèse en diminuant le nombre des projections traitées. La tomographie par rayons X a pour objectif de reconstruire la cartographie des coefficients d'atténuations d'un objet inconnu de façon non destructive. Les bases mathématiques de la tomographie repose sur la transformée de Radon et son inversion. Néanmoins des artefacts métalliques apparaissent dans les images reconstruites en inversant la transformée de Radon (la méthode de rétro-projection filtrée), un certain nombre d'hypothèse faites dans cette approche ne sont pas vérifiées. En effet, la présence de métaux exacerbe les phénomènes de durcissement de spectre et l'absence de prise en compte du rayonnement diffusé. Nous nous intéressons dans cette thèse aux méthodes itératives issues d'une méthodologie Bayésienne. Afin d'obtenir des résultats de traitement compatible avec une application clinique de nos nouvelles approches, nous avons choisi un modèle direct relativement simple et classique (linéaire) associé à des approches de corrections de données. De plus, nous avons pris en compte l'incertitude liée à la correction des données en utilisant la minimisation d'un critère de moindres carrés pondérés. Nous proposons donc une nouvelle méthode de correction du durcissement du métal sans connaissances du spectre de la source et des coefficients d'atténuation des matériaux. Nous proposons également une nouvelle méthode de correction du diffusé associée sur les mesures sous certaines conditions notamment de faible dose. En imagerie médicale par tomographie à rayons X, la surexposition ou exposition non nécessaire irradiante augmente le risque de cancer radio-induit lors d'un examen du patient. Notre deuxième axe de recherche porte donc sur la réduction de la dose en diminuant le nombre de projections. Nous avons donc introduit un nouveau mode d'acquisition possédant un échantillonnage angulaire adaptatif. On utilise pour définir cette acquisition notre connaissance a priori de l'objet. Ce mode d'acquisition associé à un algorithme de reconstruction dédié, nous permet de réduire le nombre de projections tout en obtenant une qualité de reconstruction comparable au mode d'acquisition classique. Enfin, dans certains modes d’acquisition des scanners dentaires, nous avons un détecteur qui n'arrive pas à couvrir l'ensemble de l'objet. Pour s'affranchir aux problèmes liés à la tomographie locale qui se pose alors, nous utilisons des acquisitions multiples suivant des trajectoires circulaires. Nous avons adaptés les résultats développés par l’approche « super short scan » [Noo et al 2003] à cette trajectoire très particulière et au fait que le détecteur mesure uniquement des projections tronquées. Nous avons évalué nos méthodes de réduction des artefacts métalliques et de réduction de la dose en diminuant le nombre des projections sur les données réelles. Grâce à nos méthodes de réduction des artefacts métalliques, l'amélioration de qualité des images est indéniable et il n'y a pas d'introduction de nouveaux artefacts en comparant avec la méthode de l'état de l'art NMAR [Meyer et al 2010]. Par ailleurs, nous avons réussi à réduire le nombre des projections avec notre nouveau mode d'acquisition basé sur un « super short scan » appliqué à des trajectoires multiples. La qualité obtenue est comparable aux reconstructions obtenues avec les modes d'acquisition classiques ou short-scan mais avec une réduction d’au moins 20% de la dose radioactive. / This thesis contains two main themes: development of new iterative approaches for metal artifact reduction (MAR) and dose reduction in dental CT (Computed Tomography). The metal artifacts are mainly due to the beam-hardening, scatter and photon starvation in case of metal in contrast background like metallic dental implants in teeth. The first issue concerns about data correction on account of these effects. The second one involves the radiation dose reduction delivered to a patient by decreasing the number of projections. At first, the polychromatic spectra of X-ray beam and scatter can be modeled by a non-linear direct modeling in the statistical methods for the purpose of the metal artifacts reduction. However, the reconstruction by statistical methods is too much time consuming. Consequently, we proposed an iterative algorithm with a linear direct modeling based on data correction (beam-hardening and scatter). We introduced a new beam-hardening correction without knowledge of the spectra of X-ray source and the linear attenuation coefficients of the materials and a new scatter estimation method based on the measurements as well. Later, we continued to study the iterative approaches of dose reduction since the over-exposition or unnecessary exposition of irradiation during a CT scan has been increasing the patient's risk of radio-induced cancer. In practice, it may be useful that one can reconstruct an object larger than the field of view of scanner. We proposed an iterative algorithm on super-short-scans on multiple scans in this case, which contain a minimal set of the projections for an optimal dose. Furthermore, we introduced a new scanning mode of variant angular sampling to reduce the number of projections on a single scan. This was adapted to the properties and predefined interesting regions of the scanned object. It needed fewer projections than the standard scanning mode of uniform angular sampling to reconstruct the objet. All of our approaches for MAR and dose reduction have been evaluated on real data. Thanks to our MAR methods, the quality of reconstructed images was improved noticeably. Besides, it did not introduce some new artifacts compared to the MAR method of state of art NMAR [Meyer et al 2010]. We could reduce obviously the number of projections with the proposed new scanning mode and schema of super-short-scans on multiple scans in particular case.