Topics in image reconstruction for high resolution positron emission tomography

Les problèmes mal posés représentent un sujet d'intérêt interdisciplinaire qui surgires dans la télédétection et des applications d'imagerie. Cependant, il subsiste des questions cruciales pour l'application réussie de la théorie à une modalité d'imagerie. La tomographie d'émission par positron (TEP) est une technique d'imagerie non-invasive qui permet d'évaluer des processus biochimiques se déroulant à l'intérieur d'organismes in vivo. La TEP est un outil avantageux pour la recherche sur la physiologie normale chez l'humain ou l'animal, pour le diagnostic et le suivi thérapeutique du cancer, et l'étude des pathologies dans le coeur et dans le cerveau. La TEP partage plusieurs similarités avec d'autres modalités d'imagerie tomographiques, mais pour exploiter pleinement sa capacité à extraire le maximum d'information à partir des projections, la TEP doit utiliser des algorithmes de reconstruction d'images à la fois sophistiquée et pratiques. Plusieurs aspects de la reconstruction d'images TEP ont été explorés dans le présent travail. Les contributions suivantes sont d'objet de ce travail: Un modèle viable de la matrice de transition du système a été élaboré, utilisant la fonction de réponse analytique des détecteurs basée sur l'atténuation linéaire des rayons y dans un banc de détecteur. Nous avons aussi démontré que l'utilisation d'un modèle simplifié pour le calcul de la matrice du système conduit à des artefacts dans l'image. (IEEE Trans. Nucl. Sei., 2000) );> La modélisation analytique de la dépendance décrite à l'égard de la statistique des images a simplifié l'utilisation de la règle d'arrêt par contre-vérification (CV) et a permis d'accélérer la reconstruction statistique itérative. Cette règle peut être utilisée au lieu du procédé CV original pour des projections aux taux de comptage élevés, lorsque la règle CV produit des images raisonnablement précises. (IEEE Trans. Nucl. Sei., 2001) Nous avons proposé une méthodologie de régularisation utilisant la décomposition en valeur propre (DVP) de la matrice du système basée sur l'analyse de la résolution spatiale. L'analyse des caractéristiques du spectre de valeurs propres nous a permis d'identifier la relation qui existe entre le niveau optimal de troncation du spectre pour la reconstruction DVP et la résolution optimale dans l'image reconstruite. (IEEE Trans. Nucl. Sei., 2001) Nous avons proposé une nouvelle technique linéaire de reconstruction d'image événement-par-événement basée sur la matrice pseudo-inverse régularisée du système. L'algorithme représente une façon rapide de mettre à jour une image, potentiellement en temps réel, et permet, en principe, la visualisation instantanée de distribution de la radioactivité durant l'acquisition des données tomographiques. L'image ainsi calculée est la solution minimisant les moindres carrés du problème inverse régularisé.Abstract: Ill-posed problems are a topic of an interdisciplinary interest arising in remote sensing and non-invasive imaging. However, there are issues crucial for successful application of the theory to a given imaging modality. Positron emission tomography (PET) is a non-invasive imaging technique that allows assessing biochemical processes taking place in an organism in vivo. PET is a valuable tool in investigation of normal human or animal physiology, diagnosing and staging cancer, heart and brain disorders. PET is similar to other tomographie imaging techniques in many ways, but to reach its full potential and to extract maximum information from projection data, PET has to use accurate, yet practical, image reconstruction algorithms. Several topics related to PET image reconstruction have been explored in the present dissertation. The following contributions have been made: (1) A system matrix model has been developed using an analytic detector response function based on linear attenuation of [gamma]-rays in a detector array. It has been demonstrated that the use of an oversimplified system model for the computation of a system matrix results in image artefacts. (IEEE Trans. Nucl. Sci., 2000); (2) The dependence on total counts modelled analytically was used to simplify utilisation of the cross-validation (CV) stopping rule and accelerate statistical iterative reconstruction. It can be utilised instead of the original CV procedure for high-count projection data, when the CV yields reasonably accurate images. (IEEE Trans. Nucl. Sci., 2001); (3) A regularisation methodology employing singular value decomposition (SVD) of the system matrix was proposed based on the spatial resolution analysis. A characteristic property of the singular value spectrum shape was found that revealed a relationship between the optimal truncation level to be used with the truncated SVD reconstruction and the optimal reconstructed image resolution. (IEEE Trans. Nucl. Sci., 2001); (4) A novel event-by-event linear image reconstruction technique based on a regularised pseudo-inverse of the system matrix was proposed. The algorithm provides a fast way to update an image potentially in real time and allows, in principle, for the instant visualisation of the radioactivity distribution while the object is still being scanned. The computed image estimate is the minimum-norm least-squares solution of the regularised inverse problem

Image reconstruction and processing for stationary digital tomosynthesis systems

Digital tomosynthesis (DTS) is an emerging x-ray imaging technique for disease and cancer screening. DTS takes a small number of x-ray projections to generate pseudo-3D images, it has a lower radiation and a lower cost compared to the Computed Tomography (CT) and an improved diagnostic accuracy compared to the 2D radiography. Our research group has developed a carbon nanotube (CNT) based x-ray source. This technology enables packing multiple x-ray sources into one single x-ray source array. Based on this technology, our group built several stationary digital tomosynthesis (s-DTS) systems, which have a faster scanning time and no source motion blur. One critical step in both tomosynthesis and CT is image reconstruction, which generates a 3D image from the 2D measurement. For tomosynthesis, the conventional reconstruction method runs fast but fails in image quality. A better iterative method exists, however, it is too time-consuming to be used in clinics. The goal of this work is to develop fast iterative image reconstruction algorithm and other image processing techniques for the stationary digital tomosynthesis system, improving the image quality affected by the hardware limitation. Fast iterative reconstruction algorithm, named adapted fan volume reconstruction (AFVR), was developed for the s-DTS. AFVR is shown to be an order of magnitude faster than the current iterative reconstruction algorithms and produces better images over the classical filtered back projection (FBP) method. AFVR was implemented for the stationary digital breast tomosynthesis system (s-DBT), the stationary digital chest tomosynthesis system (s-DCT) and the stationary intraoral dental tomosynthesis system (s-IOT). Next, scatter correction technique for stationary digital tomosynthesis was investigated. A new algorithm for estimating scatter profile was developed, which has been shown to improve the image quality substantially. Finally, the quantitative imaging was investigated, where the s-DCT system was used to assess the coronary artery calcium score.Doctor of Philosoph

Reports about 8 selected benchmark cases of model hierarchies : Deliverable number: D5.1 - Version 0.1

Based on the multitude of industrial applications, benchmarks for model hierarchies will be created that will form a basis for the interdisciplinary research and for the training programme. These will be equipped with publically available data and will be used for training in modelling, model testing, reduced order modelling, error estimation, efficiency optimization in algorithmic approaches, and testing of the generated MSO/MOR software. The present document includes the description about the selection of (at least) eight benchmark cases of model hierarchies.EC/H2020/765374/EU/Reduced Order Modelling, Simulation and Optimization of Coupled Systems/ROMSO

3-D lung deformation and function from respiratory-gated 4-D x-ray CT images : application to radiation treatment planning.

Many lung diseases or injuries can cause biomechanical or material property changes that can alter lung function. While the mechanical changes associated with the change of the material properties originate at a regional level, they remain largely asymptomatic and are invisible to global measures of lung function until they have advanced significantly and have aggregated. In the realm of external beam radiation therapy of patients suffering from lung cancer, determination of patterns of pre- and post-treatment motion, and measures of regional and global lung elasticity and function are clinically relevant. In this dissertation, we demonstrate that 4-D CT derived ventilation images, including mechanical strain, provide an accurate and physiologically relevant assessment of regional pulmonary function which may be incorporated into the treatment planning process. Our contributions are as follows: (i) A new volumetric deformable image registration technique based on 3-D optical flow (MOFID) has been designed and implemented which permits the possibility of enforcing physical constraints on the numerical solutions for computing motion field from respiratory-gated 4-D CT thoracic images. The proposed optical flow framework is an accurate motion model for the thoracic CT registration problem. (ii) A large displacement landmark-base elastic registration method has been devised for thoracic CT volumetric image sets containing large deformations or changes, as encountered for example in registration of pre-treatment and post-treatment images or multi-modality registration. (iii) Based on deformation maps from MOFIO, a novel framework for regional quantification of mechanical strain as an index of lung functionality has been formulated for measurement of regional pulmonary function. (iv) In a cohort consisting of seven patients with non-small cell lung cancer, validation of physiologic accuracy of the 4-0 CT derived quantitative images including Jacobian metric of ventilation, Vjac, and principal strains, (V?1, V?2, V?3, has been performed through correlation of the derived measures with SPECT ventilation and perfusion scans. The statistical correlations with SPECT have shown that the maximum principal strain pulmonary function map derived from MOFIO, outperforms all previously established ventilation metrics from 40-CT. It is hypothesized that use of CT -derived ventilation images in the treatment planning process will help predict and prevent pulmonary toxicity due to radiation treatment. It is also hypothesized that measures of regional and global lung elasticity and function obtained during the course of treatment may be used to adapt radiation treatment. Having objective methods with which to assess pre-treatment global and regional lung function and biomechanical properties, the radiation treatment dose can potentially be escalated to improve tumor response and local control

Molecular Imaging

The present book gives an exceptional overview of molecular imaging. Practical approach represents the red thread through the whole book, covering at the same time detailed background information that goes very deep into molecular as well as cellular level. Ideas how molecular imaging will develop in the near future present a special delicacy. This should be of special interest as the contributors are members of leading research groups from all over the world

Evaluation of a diffraction-enhanced imaging (DEI) prototype and exploration of novel applications for clinical implementation of DEI

Conventional mammographic image contrast is derived from x-ray absorption, resulting in breast structure visualization due to density gradients that attenuate radiation without distinction between transmitted, scattered, or refracted x-rays. Diffraction-enhanced imaging (DEI) allows for increased contrast with decreased radiation dose compared to conventional mammographic imaging due to monochromatic x-rays, its unique refraction-based contrast mechanism, and excellent scatter rejection. Although laboratory breast imaging studies have demonstrated excellent breast imaging, important clinical translation and application studies are needed before the DEI system can be established as a useful breast imaging modality. This dissertation focuses on several important studies toward the development of a clinical DEI system. First, contrast-enhanced DEI was explored using commercially available contrast agents. Phantoms were imaged at a range of x-ray energies and relevant contrast agent concentrations. Second, we performed a reader study to determine if superior DEI contrast mechanisms preserve image quality as tissue thickness increases. Breast specimens were imaged at several thicknesses, and radiologist perception of lesion visibility was recorded. Lastly, a prototype DEI system utilizing an x-ray tube source was evaluated through a reader study. Breast tissue specimens were imaged on the traditional and prototype DEI systems, and expert radiologists evaluated image quality and pathology correlation. This dissertation will demonstrate proof-of-principle for contrast-enhanced DEI, establishing the feasibility of contrast-enhanced DEI using commercially available contrast agents. Further, it will show that DEI might be able to reduce breast compression, and thus the perception of pain during mammography, without significantly decreasing breast lesion visibility. Finally, this research shows the successful implementation of a DEI prototype, displaying breast features with approximately statistically equivalent visibility to the traditional DEI system. Together, this research is an important step toward the clinical translation of DEI, a technology with the potential to facilitate early breast cancer detection and diagnosis

2022 Review of Data-Driven Plasma Science

Data-driven science and technology offer transformative tools and methods to science. This review article highlights the latest development and progress in the interdisciplinary field of data-driven plasma science (DDPS), i.e., plasma science whose progress is driven strongly by data and data analyses. Plasma is considered to be the most ubiquitous form of observable matter in the universe. Data associated with plasmas can, therefore, cover extremely large spatial and temporal scales, and often provide essential information for other scientific disciplines. Thanks to the latest technological developments, plasma experiments, observations, and computation now produce a large amount of data that can no longer be analyzed or interpreted manually. This trend now necessitates a highly sophisticated use of high-performance computers for data analyses, making artificial intelligence and machine learning vital components of DDPS. This article contains seven primary sections, in addition to the introduction and summary. Following an overview of fundamental data-driven science, five other sections cover widely studied topics of plasma science and technologies, i.e., basic plasma physics and laboratory experiments, magnetic confinement fusion, inertial confinement fusion and high-energy-density physics, space and astronomical plasmas, and plasma technologies for industrial and other applications. The final section before the summary discusses plasma-related databases that could significantly contribute to DDPS. Each primary section starts with a brief introduction to the topic, discusses the state-of-the-art developments in the use of data and/or data-scientific approaches, and presents the summary and outlook. Despite the recent impressive signs of progress, the DDPS is still in its infancy. This article attempts to offer a broad perspective on the development of this field and identify where further innovations are required

Argonne National Laboratory Annual Report of Laboratory Directed Research and Development Program Activities for FY 1994

The purposes of Argonne's Laboratory Directed Research and Development (LDRD) Program are to encourage the development of novel concepts, enhance the Laboratory's R and D capabilities, and further the development of its strategic initiatives. Projects are selected from proposals for creative and innovative R and D studies which are not yet eligible for timely support through normal programmatic channels. Among the aims of the projects supported by the Program are establishment of engineering proof-of-principle; assessment of design feasibility for prospective facilities; development of an instrumental prototype, method, or system; or discovery in fundamental science. Several of these projects are closely associated with major strategic thrusts of the Laboratory as described in Argonne's Five-Year Institutional Plan, although the scientific implications of the achieved results extend well beyond Laboratory plans and objectives. The projects supported by the Program are distributed across the major programmatic areas at Argonne as indicated in the Laboratory's LDRD Plan for FY 1994. Project summaries of research in the following areas are included: (1) Advanced Accelerator and Detector Technology; (2) X-ray Techniques for Research in Biological and Physical Science; (3) Nuclear Technology; (4) Materials Science and Technology; (5) Computational Science and Technology; (6) Biological Sciences; (7) Environmental Sciences: (8) Environmental Control and Waste Management Technology; and (9) Novel Concepts in Other Areas