Biomedical optical imaging is capable of providing functional information of the soft bi-ological tissues, whose applications include imaging large tissues, such breastand brain in-vivo. Biomedical optical imaging uses near infrared light (600nm-900nm) as the probing media, givin ganaddedadvantageofbeingnon-ionizingimagingmodality. The tomographic technologies for imaging large tissues encompasses diffuse optical tomogra-phyandphotoacoustictomography. Traditional image reconstruction methods indiffuse optical tomographyemploysa �2-norm based regularization, which is known to remove high frequency no is either econstructed images and make the mappearsmooth. Hence as parsity based image reconstruction has been deployed for diffuse optical tomography, these sparserecov-ery methods utilize the �p-norm based regularization in the estimation problem with 0≤ p<1. These sparse recovery methods, along with an approximation to utilizethe �0-norm, have been used forther econstruction of diffus eopticaltomographic images.The comparison of these methods was performed by increasing the sparsityinthesolu-tion. Further a model resolution matrix based framework was proposed and shown to in-duceblurinthe�2-norm based regularization framework for diffuse optical tomography. This model-resolution matrix framework was utilized in the optical imaged econvolution framework. A basis pursuitdeconvolution based on Split AugmentedLagrangianShrink-ageAlgorithm(SALSA)algorithm was used along with the Tikhonovregularization step making the image reconstruction into a two-step procedure. This new two-step approach was found to be robust with no iseandwasabletobetterdelineatethestructureswhichwasevaluatedusingnumericalandgelatinphantom experiments. Modern diffuse optical imaging systems are multi-modalin nature, where diffuse optical imaging is combined with traditional imaging modalitiessuc has Magnetic Res-onanceImaging(MRI),or Computed Tomography(CT). Image-guided diffuse optical tomography has the advantage of reducingthetota lnumber of optical parameters beingreconstructedtothenumber of distinct tissue types identified by the traditional imaging modality, converting the optical image-reconstruction problem fromunder-determined innaturetoover-determined. In such cases, the minimum required measurements might be farless compared to those of the traditional diffuse optical imaging. An approach to choose these measurements optimally based on a data-resolution matrix is proposed, and it is shown that it drastically reduces the minimum required measurements (typicalcaseof240to6) without compromising the image reconstruction performance. In the last part of the work , a model-based image reconstruction approaches in pho-toacoustic tomography (which combines light and ultra sound) arestudied as it is know that these methods have a distinct advantage compared to traditionalanalytical methods in limited datacase. These model-based methods deployTikhonovbasedregularizationschemetoreconstruct the initial pressure from the boundary acoustic data. Again a model-resolution for these cases tend to represent the blurinduced by the regularization scheme. A method that utilizes this blurringmodelandper forms the basis pursuit econ-volution to improve the quantitative accuracy of the reconstructed photoacoustic image is proposed and shown to be superior compared to other traditional methods. Moreover, this deconvolution including the building of model-resolution matrixis achievedvia the Lanczosbidiagonalization (least-squares QR) making this approach computationally ef-ficient and deployable inreal-time. Keywords Medical imaging, biomedical optical imaging, diffuse optical tomography, photoacous-tictomography, multi-modalimaging, inverse problems,sparse recovery,computational methods inbiomedical optical imaging.

Diffuse optical tomography uses near infrared (NIR) light as the probing media to recover the distributions of tissue optical properties. It has a potential to become an adjunct imaging modality for breast and brain imaging, that is capable of providing functional information of the tissue under investigation. As NIR light propagation in the tissue is dominated by scattering, the image reconstruction problem (inverse problem) tends to be non-linear and ill-posed, requiring usage of advanced computational methods to compensate this. Traditional image reconstruction methods in diffuse optical tomography employ l2 –norm based regularization, which is known to remove high frequency noises in the re-constructed images and make them appear smooth. The recovered contrast in the reconstructed image in these type of methods are typically dependent on the iterative nature of the method employed, in which the non-linear iterative technique is known to perform better in comparison to linear techniques. The usage of non-linear iterative techniques in the real-time, especially in dynamical imaging, becomes prohibitive due to the computational complexity associated with them. In the rapid dynamic diffuse optical imaging, assumption of a linear dependency in the solutions between successive frames results in a linear inverse problem. This new frame work along with the l1–norm based regularization can provide better robustness to noise and results in a better contrast recovery compared to conventional l2 –based techniques. Moreover, it is shown that the proposed l1-based technique is computationally efficient compared to its counterpart(l2 –based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames. Modern diffuse optical imaging systems are multi-modal in nature, where diffuse optical imaging is combined with traditional imaging modalities such as MRI, CT, and Ultrasound. A novel approach that can more effectively use the structural information provided by the traditional imaging modalities in these scenarios is introduced, which is based on prior image constrained- l1 minimization scheme. This method has been motivated by the recent progress in the sparse image reconstruction techniques. It is shown that the- l1 based frame work is more effective in terms of localizing the tumor region and recovering the optical property values both in numerical and gelatin phantom cases compared to the traditional methods that use structural information.

Diffuse optical tomography (DOT) is one of the promising imaging modalities that pro- vides functional information of the soft biological tissues in-vivo, such as breast and brain tissues. The near infrared (NIR) light (600-1000 nm) is the interrogating radiation, which is typically delivered and collected using fiber bundles placed on the boundary of the tissue. The internal optical property distribution is estimated via model-based image reconstruction algorithm using these limited boundary measurements. Image reconstruction problem in DOT is known to be non-linear, ill-posed, and some times under-determined due to the multiple scattering of NIR light in the tissue. Solving this inverse problem requires regularization to obtain meaningful results, with Tikhonov-type regularization being the most popular one. The choice of the regularization parameter dictates the reconstructed optical image quality and is typically chosen empirically or based on prior experience. An automated method for optimal selection of regularization parameter that is based on regularized minimal residual method (MRM) is proposed and is compared with the traditional generalized cross-validation method. The results obtained using numerical and gelatin phantom data indicate that the MRM-based method is capable of providing the optimal regularization parameter. A new approach that can easily incorporate any generic penalty function into the diffuse optical tomographic image reconstruction is introduced to show the utility of non-quadratic penalty functions. The penalty functions that were used include, quadratic (`2), absolute (`1), Cauchy, and Geman-McClure. The regularization parameter in each of these cases were obtained automatically using the generalized cross-validation (GCV) method. The reconstruction results were systematically compared with each other via utilization of quantitative metrics, such as relative error and Pearson correlation. The reconstruction results indicate that while quadratic penalty may be able to provide better separation between two closely spaced targets, it's contrast recovery capability is limited and the sparseness promoting penalties, such as `1, Cauchy, Geman-McClure have better utility in reconstructing high-contrast and complex-shaped targets with Geman-McClure penalty being the most optimal one. Effective usage of image guidance by incorporating the refractive index (RI) variation in computational modeling of light propagation in tissue is investigated to assess its impact on optical-property estimation. With the aid of realistic patient breast three-dimensional models, the variation in RI for different regions of tissue under investigation is shown to influence the estimation of optical properties in image-guided diffuse optical tomography (IG-DOT) using numerical simulations. It is also shown that by assuming identical RI for all regions of tissue would lead to erroneous estimation of optical properties. The a priori knowledge of the RI for the segmented regions of tissue in IG-DOT, which is difficult to obtain for the in vivo cases, leads to more accurate estimates of optical properties. Even inclusion of approximated RI values, obtained from the literature, for the regions of tissue resulted in better estimates of optical properties, with values comparable to that of having the correct knowledge of RI for different regions of tissue. Image reconstruction in IG-DOT procedure involves reduction of the number of optical parameters to be reconstructed equal to the number of distinct regions identified in the structural information provided by the traditional imaging modality. This makes the image reconstruction problem to be well-determined compared to traditional under- determined case. Still, the methods that are deployed in this case are same as the one used for traditional diffuse optical image reconstruction, which involves regularization term as well as computation of the Jacobian. A gradient-free Nelder-Mead simplex method was proposed here to perform the image reconstruction procedure and shown to be providing solutions that are closely matching with ones obtained using established methods. The proposed method also has the distinctive advantage of being more efficient due to being regularization free, involving only repeated forward calculations.

[ES] Desde su creación en la década de 1950, las imágenes tomográficas han resultado muy valiosas en el ámbito médico ayudando tanto en el diagnóstico como en el tratamiento de múltiples enfermedades. Dentro de la imagen molecular, los escáneres PET (Tomografía por Emisión de Positrones) generan información detallada de la interacción de los radio-trazadores con el tejido de estudio, pudiendo combinar dicha información con imagen anatómica de escáneres TC (Tomografía Computarizada) o RM (Resonancia Magnética). Con el fin de aumentar las prestaciones de estos equipos, como la sensibilidad y la resolución espacial, los PET de cuerpo completo recientemente aumentan su cobertura axial. Sin embargo, el precio de estos dispositivos se multiplica, dificultando su compra en muchos hospitales y centros de investigación. Como alternativa, los escáneres PET específicos de órganos manejan un menor número de detectores haciéndolos más económicos. El objetivo de este tipo de escáneres es mejorar el rendimiento de los dispositivos acercando los detectores al paciente lo máximo posible, optimizando su diseño para un órgano en específico. Otra ventaja es la posible portabilidad de los aparatos. En esta tesis introducimos dos posibles diseños de PET específicos orientados a distintos órganos y con diferente tecnología y geometría y además un escáner preclínico con una geometría novedosa. El primer escáner fue construido de un proyecto nacional llamado PROSPET, fue diseñado y optimizado para hacer imagen de la próstata, debido a la conocida elevada tasa de cáncer de próstata en hombres. El 17% de la población masculina sufrirá cáncer de próstata. El detector escogido para este diseño está compuesto por cristales centelladores monolíticos acoplados a una matriz de fotomultiplicadores de silicio. Inicialmente se pensó en crear un escáner compuesto por dos palas. Sin embargo, los resultados con pacientes no fueron satisfactorios debido a la falta de información angular y la ausencia de información temporal precisa en los detectores. Por tanto, se construyó una configuración de anillo con un diámetro reducido en comparación con escáneres de cuerpo completo. Se apreció un aumento en la sensibilidad y la resolución espacial, así como una buena calidad de imagen utilizando fantomas. El segundo escáner, llamado proyecto CardioPET, está orientado a visualizar el corazón cuando el paciente está sometido a condiciones de estrés farmacológico. Para este dispositivo se utilizó el diseño de dos palas, pero usando cristales pixelados, mejorando la resolución temporal, permitiendo implantar algoritmos de tiempo de vuelo. Se han montado y testeado dos palas tanto con simulaciones como experimentalmente con buenas prestaciones. Además, se procedió a registrar el movimiento de las fuentes de radiación con el fin de aplicar correcciones de movimiento con la ayuda de una cámara externa y unos marcadores ARUCO. Los algoritmos de corrección de movimiento fueron testeados, demostrando un buen funcionamiento. El último dispositivo fue diseñado para optimizar la configuración PET de anillo lo máximo posible. Para ello, se eliminaron los espaciados entre detectores en un escáner pequeño de animales, creando un único detector centellador de forma cilíndrica. Con esto se busca aumentar la sensibilidad, pues ya no se pierden interacciones en los huecos, y también la resolución espacial. Dos prototipos fueron testeados con simulaciones, y validados experimentalmente. El primero con caras de salida planas y el segundo totalmente cilíndrico. En ambos diseños se observaron efectos debidos a la curvatura del detector que necesariamente han de ser compensados con una calibración. / [CA] Des de la seua creació en la dècada de 1950, les imatges tomogràfiques hi han resultat molt valuoses en àmbit mèdic ajudant tant en el diagnòstic com en el tractament de moltes malalties. Dins de la imatge molecular, els escàners PET (Tomografia per Emissió de Positrons) generen informació detallada de la interacció dels traçadors amb el teixit del pacient, podent combinar aquesta informació amb imatge anatòmica d'escàners TC (Tomografia Axial Automatitzada) o RM (Ressonancia Magnètica). Amb el fi d'augmentar les prestacions d’aquests equips, els PET de cos complet augmenten la seua cobertura axial, multiplicant el preu dels dispositius i dificultant la seua compra en hospitals i centres d’investigació. Com a alternativa, els escàners PET específics d'òrgans utilitzen un menor nombre de detectors resultant així un preu més econòmic. Un altre avantatge és la possible portabilitat dels aparells. En aquesta tesi abordem tres possibles dissenys de PET específics orientats a diferents òrgans i amb diferent tecnologia i geometria. El primer de tots, un projecte nacional denominat PROSPET, ha sigut dissenyat i optimitzat per a fer imatge de la pròstata, ja que és molt coneguda l'elevada taxa de càncer de pròstata en homes. El 17% de población masculina patirà càncer de pròstata. El detector escollit per a aquest disseny està format per cristals centellejadors monolítics acoblats a una matriu de fotomultiplicadors de silici. De primeres es va pensar a crear un escàner compost per dues pales, ja que permetria disposar els detectors molt a prop del pacient. El resultat no va ser molt satisfactori a causa de la falta d'informació angular i l'absència d'informació temporal precisa. Per tant, l'última iteració va consistir en una configuració d'anell amb un diàmetre reduït en comparació amb els escàners de cos complet. Es va observar una millora en la sensibilitat i la resolució espacial, així com una qualitat d'imatge acceptable. El segon dispositiu va ser dissenyat per a optimitzar la configuració d'anell el màxim possible. Per això es van llevar els espaiats entre detectors, creant un únic detector de forma cilíndrica. Amb aquest disseny es busca augmentar la sensibilitat, ja que no es perden interaccions en els espaiats, i també la resolució espacial. Dos prototips van ser testejats amb simulacions i validats experimentalment. El primer amb cares d'eixida planars i el segon totalment cilíndric. En els dos dissenys es va observar efectes deguts a la curvatura del detector que necessàriament ha de ser compensat amb una calibració. L’últim escàner, denominat projecte CardioPET, està orientat a visualitzar el cor durant el pacient quan és sotmés a condicions d'estrés farmacologic. escàner, denominat projecte CardioPET, està orientat a visualitzar el cor durant el pacient quan és sotmés a condicions d'estrés. Es va recuperar el disseny de les pales per aquest dispositiu, però utilitzant cristals pixelats, millorant la resolució temporal. Dues pales van ser muntades i testejades tant amb simulacions com experimentalment amb bones prestacions. A més, es va registrar el moviment de les fonts de radiació amb la fi d'aplicar correcció de moviment amb l'ajuda d'una càmera externa i uns marcadors ARUCO. Els algoritmes de correcció de moviment també van ser testejats, demostrant un bon funcionament. L'últim dispositiu va ser dissenyat per a optimitzar la configuració d'anell el màxim possible. Per això es van llevar els espaiats entre detectors, creant un únic detector de forma cilíndrica. Amb aquest disseny es busca augmentar la sensibilitat, ja que no es perden interaccions en els espaiats, i també la resolució espacial. Dos prototips van ser testejats amb simulacions i validats experimentalment. El primer amb cares d'eixida planars i el segon totalment cilíndric. En els dos dissenys es va observar efectes deguts a la curvatura del detector que necessàriament ha de ser compensat amb una calibració. / [EN] Since their introduction in the 1950-decade, tomographic images have become very valuable in the medical field helping both in diagnostics and in a variety of illnesses treatment. In the molecular imaging field, Positron Emission Tomography (PET) provides accurate information of the radio-tracers interactions with the patient tissue. Moreover, it is possible to combine this information with anatomical images provided by CT (Computed Tomography) or MR (Magnetic Resonance) scanners. With the aim to improve PET systems performance, such as the spatial resolution and the sensitivity, whole body (WB) PET scanners with large axial coverage are recently proposed. However, the system cost increases and, thus, makes difficult their installation in many hospitals or research centers. Organ-dedicated PET scanners, as an alternative to such large systems, use a lower number of detectors, so their price is considerably more economical. The goal of this kind of systems is to boost PET performance by placing the detectors as close as possible to the patient, optimizing the design for a specific organ instead of a large volume. Other advantage of these scanners is their portability. In this thesis we have worked in the design and validation of two organ-dedicated PET scanners with different geometries and technologies, as well as in a novel pre-clinical PET. The first scanner was the result from a national project called PROSPET. A PET system was designed and optimized to image the prostate area. Notice there is a high incidence rate of prostate cancer in the male population. 17% of male population will suffer prostate cancer. For this scanner, the detector modules were composed by a monolithic LYSO scintillation block coupled to a photosensor array based on silicon photomultipliers (SiPM). The first design configuration was made by two panels. However, patient results were not satisfactory due to the lack of angular information and the poor detector time resolution. Therefore, it was rebuilt in a ring configuration with a reduced diameter in comparison with WB-PET scanners. A high sensitivity and spatial resolution were found, as well as a good image quality using phantoms. The second PET scanner, called CardioPET, also arose from a national grant, and it was implemented to visualize the heart area when the patient is under stress condition. The two panels geometry was also implemented for this system, but using pixelated crystals, therefore improving the detector time resolution and allowing to use time of flight (TOF) reconstruction algorithms. Two panels were mounted and tested with both simulation and experimental data with good results. Furthermore, the patient motion was registered applying movement correction techniques with the help of an external optical camera device and ARUCO markers. These algorithms were tested showing a good performance. The last device that we worked within this PhD thesis was designed to optimize the classical ring PET configuration as much as possible. To do so, the gaps between the detector modules in a small animal PET were eliminated by building a single detector with a cylindrical scintillator shape. The goal is to improve the sensitivity, given that there are no event losses in the gaps and to also boost the spatial resolution since there are not edges. Two prototypes were tested with simulations, and experimentally validated as well. The first of them was built with planar outer faces whereas the second was fully cylindrical. In both designs some effects originated from the detector curvature were observed and successfully corrected during the calibration. / This thesis was supported by a FPI grant under 2017-08582 reference in the PhD program: “Programa de Doctorado en Tecnologías para la Salud y el Bienestar” belonging to the Polytechnic University of Valencia. The grant was supported by the “Consejo Superior de Investigaciones Científicas” together with the “Agencia Estatal de Investigación” and the “Fondo Social Europeo”. / Cañizares Ledo, G. (2022). Characterization of Dedicated PET Equipment with Non-Conventional Geometry [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/184977

Thesis (MA (African Languages))--University of Stellenbosch, 2009. / The purpose of this study is to examine message production and image restoration in the narratives of isiXhosa-speaking farming communities. According to Gergen (1994), narrative forms – such as the stability narrative, progressive narrative and regressive narrative – are linguistic tools that have important social functions to fulfil. Gergen (1994) further indicates that self-narratives are social processes in which individuals are realised on the personal perspective or experience. The self-narratives used and analysed in this study portray the contemporary, truth-based elements of a well-formed narrative. Narrative accounts are also embedded within social action; they render events socially visible and typically establish expectations for future events because the events of daily life are immersed in narrative. The study starts by laying the foundation for the reasons why human beings tell stories and why stories are so important in people’s daily lives, since most people begin their encounters with stories at childhood. Possibly because of this intimate and long-standing acquaintance with stories from childhood, stories also serve as critical means by which human beings make themselves intelligible within the social world. This study further examines the motivations and conditions for account-giving in isiXhosa. Accounts are similar to narratives and can be retained at the level of private reflections for others to read, to be educated and to learn from and to refer to from time to time. Gergen (1994) considers self-narratives as forms of social accounting or public discourse. In this sense, narratives are conversational resources, their construction open to continuous alteration as interaction progresses. The study elaborates on this phenomenon, especially in the narrative accounts of the various isiXhosa stories that were collected and analysed. What emerges from the analyses is that the individual characters whose stories are told are portrayed as moving through their experience, dealing with some conflict or problem in their lives and, at the same time, searching for a resolution. It also emerges from the collection of these various isiXhosa narratives that they sharpen our understanding of the major stressful situations in each person’s mind and how the individual reasons about the difficulties encountered in life. The narratives prove, in this regard, to be a cultural resource that serves social purposes, such as self-identification, self-justification, self criticism and social solidification. In this sense then, for an account to be true, it has to be goal-orientated and relate to people’s day-to-day lives. The study finds that the social-interactive aspects of account-giving involve severe reproach forms, including personal attacks and derogatory aspects, which elicit defensive reactions resulting in negative interpersonal and emotional consequences.

No description available.

The purpose of this work is to present the development and validation of a novel method for reconstructing time-dependent, or 4D, cone-beam CT (4DCBCT) images. 4DCBCT can have a variety of applications in the radiotherapy of moving targets, such as lung tumors, including treatment planning, dose verification, and real time treatment adaptation. However, in its current incarnation it suffers from poor reconstruction quality and limited temporal resolution that may restrict its efficacy. Our algorithm remedies these issues by deforming a previously acquired high quality reference fan-beam CT (FBCT) to match the projection data in the 4DCBCT data-set, essentially creating a 3D animation of the moving patient anatomy. This approach combines the high image quality of the FBCT with the fine temporal resolution of the raw 4DCBCT projection data-set. Deformation of the reference CT is accomplished via a patient specific motion model. The motion model is constrained spatially using eigenvectors generated by a principal component analysis (PCA) of patient motion data, and is regularized in time using parametric functions of a patient breathing surrogate recorded simultaneously with 4DCBCT acquisition. The parametric motion model is constrained using forward iterative projection matching (FIPM), a scheme which iteratively alters model parameters until digitally reconstructed radiographs (DRRs) cast through the deforming CT optimally match the projections in the raw 4DCBCT data-set. We term our method FIPM-PCA 4DCBCT. In developing our algorithm we proceed through three stages of development. In the first, we establish the mathematical groundwork for the algorithm and perform proof of concept testing on simulated data. In the second, we tune the algorithm for real world use; specifically we improve our DRR algorithm to achieve maximal realism by incorporating physical principles of image formation combined with empirical measurements of system properties. In the third stage we test our algorithm on actual patient data and evaluate its performance against gold standard and ground truth data-sets. In this phase we use our method to track the motion of an implanted fiducial marker and observe agreement with our gold standard data that is typically within a millimeter.

Approved for public release; distribution in unlimited. / PC and MNF transforms are two widely used methods that are utilized for various applications such as dimensionality reduction, data compression and noise reduction. In this thesis, an in-depth study of these two methods is conducted in order to estimate their performance in hyperspectral imagery. First the PCA and MNF methods are examined for their effectiveness in image enhancement. Also, the various methods are studied to evaluate their ability to determine the intrinsic dimension of the data. Results indicate that, in most cases, the scree test gives the best measure of the number of retained components, as compared to the cumulative variance, the Kaiser, and the CSD methods. Then, the applicability of PCA and MNF for image restoration are considered using two types of noise, Gaussian and periodic. Hyperspectral images are corrupted by noise using a combination of ENVI and MATLAB software, while the performance metrics used for evaluation of the retrieval algorithms are visual interpretation, rms correlation coefficient spectral comparison, and classification. In Gaussian noise, the retrieved images using inverse transforms indicate that the basic PC and MNF transform perform comparably. In periodic noise, the MNF transform shows less sensitivity to variations in the number of lines and the gain factor. / Lieutenant, Hellenic Navy

Since the birth of charge coupled devices (CCD) and the complementary metal-oxide-semiconductor (CMOS) active pixel sensors, pixel pitch of digital image sensors has been continuously shrinking to meet the resolution and size requirements of the cameras. However, shrinking pixels reduces the maximum number of photons a sensor can hold, a phenomenon broadly known as the full-well capacity limit. The drop in full-well capacity causes drop in signal-to-noise ratio and dynamic range.<div><br></div><div>The Quanta Image Sensor (QIS) is a class of solid-state image sensors proposed by Eric Fossum in 2005 as a potential solution for the limited full-well capacity problem. QIS is envisioned to be the next generation image sensor after CCD and CMOS since it enables sub-diffraction-limit pixels without the inherited problems of pixel shrinking. Equipped with a massive number of detectors that have single-photon sensitivity, the sensor counts the incoming photons and triggers a binary response “1” if the photon count exceeds a threshold, or “0” otherwise. To acquire an image, the sensor oversamples the space and time to generate a sequence of binary bit maps. Because of this binary sensing mechanism, the full-well capacity, signal-to-noise ratio and the dynamic range can all be improved using an appropriate image reconstruction algorithm. The contribution of this thesis is to address three image processing problems in QIS: 1) Image reconstruction, 2) Threshold design and 3) Color filter array design.</div><div><br></div><div>Part 1 of the thesis focuses on reconstructing the latent grayscale image from the QIS binary measurements. Image reconstruction is a necessary step for QIS because the raw binary measurements are not images. Previous methods in the literature use iterative algorithms which are computationally expensive. By modeling the QIS binary measurements as quantized Poisson random variables, a new non-iterative image reconstruction method based on the Transform-Denoise framework is proposed. Experimental results show that the new method produces better quality images while requiring less computing time.</div><div><br></div><div>Part 2 of the thesis considers the threshold design problem of a QIS. A spatially-varying threshold can significantly improve the reconstruction quality and the dynamic range. However, no known method of how to achieve this can be found in the literature. The theoretical analysis of this part shows that the optimal threshold should match with the underlying pixel intensity. In addition, the analysis proves the existence of a set of thresholds around the optimal threshold that give asymptotically unbiased reconstructions. The asymptotic unbiasedness has a phase transition behavior. A new threshold update scheme based on this idea is proposed. Experimentally, the new method can provide good estimates of the thresholds with less computing budget compared to existing methods.</div><div><br></div><div>Part 3 of the thesis extends QIS capabilities to color imaging by studying how a color filter array should be designed. Because of the small pixel pitch of QIS, crosstalk between neighboring pixels is inevitable and should be considered when designing the color filter arrays. However, optimizing the light efficiency while suppressing aliasing and crosstalk in a color filter array are conflicting tasks. A new optimization framework is proposed to solve the problem. The new framework unifies several mainstream design criteria while offering generality and flexibility. Extensive experimental comparisons demonstrate the effectiveness of the framework.</div>

A perfilagem de colunas por raios gama (column gamma scan) é uma técnica nuclear empregada para solucionar problemas em equipamentos de processos industriais, nas refinarias e petroquímicas. Consiste na utilização de uma fonte selada e um detector de radiação [NaI(Tl)], obtendo-se o perfil de densidade unidimensional (1D) do equipamento. Nas últimas décadas, ocorreram algumas melhorias na técnica de perfilagem, tais como, na digitalização contínua das informações e nos sistemas de detecção da radiação (wireless). Novos aplicativos melhoraram a qualidade da apresentação dos resultados. Entretanto, a condição da técnica não mudou drasticamente, desde sua criação. Seu resultado é simplesmente um gráfico 1D da densidade média, em função da altura do equipamento industrial. A tecnologia inovadora proposta neste trabalho de Mestrado utiliza a reconstrução tomográfica industrial, via algoritmos iterativos derivados da ART (Algebraic Reconstruction Technique) e do MART (Multiplicative Algebraic Reconstruction Technique), para apresentar o resultado de perfilagem como uma imagem bidimensional (2D) da distribuição de densidade, ao invés de um gráfico 1D. Nitidamente, uma imagem 2D possui mais informações técnicas do equipamento em análise, permitindo um avanço na tecnologia de ensaios não destrutivos (END). Assim, muitos problemas operacionais não detectáveis em equipamentos de processos industriais podem ser descobertos e solucionados de forma on-line, usando-se o imageamento 2D. Esta tecnologia permitiu que um pedido de patente fosse depositado junto ao Instituto Nacional de Propriedade Industrial (INPI). / Column gamma scan is one of the most common nuclear techniques on troubleshooting industrial process equipments like distillation columns and reactors. With a very simple concept, the technique is easy to implement. Searching for a competitive edge the industry has been long developing solutions to achieve better results. On the last decades, significant development has been done with the advent of new hardware, electronics, portable computers and software. Continuous scanning and wireless detection systems are examples of successful field solutions, while new software aid on reporting and data presentation. However the type and quality of the results itself has not dramatically changed since its beginning. A scan profile is simple to understand, although the process to build it can be very complex as it requires a specific blend of knowledge and abilities. Process engineering, chemical engineering, internal hydraulic project, nuclear engineering and field abilities are pre requisites for of any scan specialist. Correct data gathering, interpretation and reporting are abilities often difficult to match or requires a long time of training. The industry faces a similar difficult on the customer side, as it is always necessary to train end users to understand a report and how to use its best. This scientific work describes our effort on developing a new approach on the gamma column scan test using image reconstruction techniques that would result on a graphic image rather than a XY plot. Direct and easier to understand, a report with graphic images would be also be accessible to a wider audience, not limited to the customers experienced with gamma scan interpretation.