Evaluation of Motion Artifact Metrics for Coronary CT Angiography

Purpose This study quantified the performance of coronary artery motion artifact metrics relative to human observer ratings. Motion artifact metrics have been used as part of motion correction and best‐phase selection algorithms for Coronary Computed Tomography Angiography (CCTA). However, the lack of ground truth makes it difficult to validate how well the metrics quantify the level of motion artifact. This study investigated five motion artifact metrics, including two novel metrics, using a dynamic phantom, clinical CCTA images, and an observer study that provided ground‐truth motion artifact scores from a series of pairwise comparisons. Method Five motion artifact metrics were calculated for the coronary artery regions on both phantom and clinical CCTA images: positivity, entropy, normalized circularity, Fold Overlap Ratio (FOR), and Low‐Intensity Region Score (LIRS). CT images were acquired of a dynamic cardiac phantom that simulated cardiac motion and contained six iodine‐filled vessels of varying diameter and with regions of soft plaque and calcifications. Scans were repeated with different gantry start angles. Images were reconstructed at five phases of the motion cycle. Clinical images were acquired from 14 CCTA exams with patient heart rates ranging from 52 to 82 bpm. The vessel and shading artifacts were manually segmented by three readers and combined to create ground‐truth artifact regions. Motion artifact levels were also assessed by readers using a pairwise comparison method to establish a ground‐truth reader score. The Kendall\u27s Tau coefficients were calculated to evaluate the statistical agreement in ranking between the motion artifacts metrics and reader scores. Linear regression between the reader scores and the metrics was also performed. Results On phantom images, the Kendall\u27s Tau coefficients of the five motion artifact metrics were 0.50 (normalized circularity), 0.35 (entropy), 0.82 (positivity), 0.77 (FOR), 0.77(LIRS), where higher Kendall\u27s Tau signifies higher agreement. The FOR, LIRS, and transformed positivity (the fourth root of the positivity) were further evaluated in the study of clinical images. The Kendall\u27s Tau coefficients of the selected metrics were 0.59 (FOR), 0.53 (LIRS), and 0.21 (Transformed positivity). In the study of clinical data, a Motion Artifact Score, defined as the product of FOR and LIRS metrics, further improved agreement with reader scores, with a Kendall\u27s Tau coefficient of 0.65. Conclusion The metrics of FOR, LIRS, and the product of the two metrics provided the highest agreement in motion artifact ranking when compared to the readers, and the highest linear correlation to the reader scores. The validated motion artifact metrics may be useful for developing and evaluating methods to reduce motion in Coronary Computed Tomography Angiography (CCTA) images

MR Image Based Approach for Metal Artifact Reduction in X-Ray CT

For decades, computed tomography (CT) images have been widely used to discover valuable anatomical information. Metallic implants such as dental fillings cause severe streaking artifacts which significantly degrade the quality of CT images. In this paper, we propose a new method for metal-artifact reduction using complementary magnetic resonance (MR) images. The method exploits the possibilities which arise from the use of emergent trimodality systems. The proposed algorithm corrects reconstructed CT images. The projected data which is affected by dental fillings is detected and the missing projections are replaced with data obtained from a corresponding MR image. A simulation study was conducted in order to compare the reconstructed images with images reconstructed through linear interpolation, which is a common metal-artifact reduction technique. The results show that the proposed method is successful in reducing severe metal artifacts without introducing significant amount of secondary artifacts

The Estimation and Correction of Rigid Motion in Helical Computed Tomography

X-ray CT is a tomographic imaging tool used in medicine and industry. Although technological developments have significantly improved the performance of CT systems, the accuracy of images produced by state-of-the-art scanners is still often limited by artefacts due to object motion. To tackle this problem, a number of motion estimation and compensation methods have been proposed. However, no methods with the demonstrated ability to correct for rigid motion in helical CT scans appear to exist. The primary aims of this thesis were to develop and evaluate effective methods for the estimation and correction of arbitrary six degree-of-freedom rigid motion in helical CT. As a first step, a method was developed to accurately estimate object motion during CT scanning with an optical tracking system, which provided sub-millimetre positional accuracy. Subsequently a motion correction method, which is analogous to a method previously developed for SPECT, was adapted to CT. The principle is to restore projection consistency by modifying the source-detector orbit in response to the measured object motion and reconstruct from the modified orbit with an iterative reconstruction algorithm. The feasibility of this method was demonstrated with a rapidly moving brain phantom, and the efficacy of correcting for a range of human head motions acquired from healthy volunteers was evaluated in simulations. The methods developed were found to provide accurate and artefact-free motion corrected images with most types of head motion likely to be encountered in clinical CT imaging, provided that the motion was accurately known. The method was also applied to CT data acquired on a hybrid PET/CT scanner demonstrating its versatility. Its clinical value may be significant by reducing the need for repeat scans (and repeat radiation doses), anesthesia and sedation in patient groups prone to motion, including young children

Truncation artifact correction for micro-CT scanners

The work included in this project is framed on one of the lines of research carried out at the Laboratorio de Imagen Médica de la Unidad de Medicina y Cirugía Experimental (UMCE) of Hospital General Universitario Gregorio Marañón and the Bioengineering and Aerospace Department of Universidad Carlos III de Madrid. Its goal is to design, develop and evaluate new data acquisition systems, processing and reconstruction of multimodal images for application in preclinical research. Inside this research line, an x-ray computed tomography (micro-CT add on) system of high resolution has been designed for small animal. Nowadays, computed tomography (CT) is one of the techniques most widely used to obtain anatomical information from living subjects. Different artifacts from different nature usually degrade the qualitative and quantitative analysis of these images. This creates the urgent need of developing algorithms to compensate and/or reduce these artifacts. The general objective of the present thesis is to implement a method for compensating truncation artifact in the micro-CT add-on scanner for small animal developed at Hospital Universitario Gregorio Marañón. This artifact appears due to the acquisition of incomplete x-ray projections when part of the sample, especially obese rats, lies outside the field of view. As a result of these data inconsistencies, bright shading artifacts and quantification errors in the images may appear after the reconstruction process. First of all, truncation artifact in the high resolution micro-CT add-on scanner was studied. Then, after a review of the proposed methods in the literature, the optimal approach for the micro-CT add-on was selected, based on a sinogram extrapolation technique developed by Ohnesorge et al [1]. This method consists on a symmetric mirroring extrapolation of the truncated projections that guarantees continuity at the truncation point. It includes a sine shaping effect that ensures a smooth attenuation signal drop. Truncation artifact correction method has been validated in simulated and real studies. Results show an overall significant reduction of truncation artifact. This algorithm has been adapted and implemented in the reconstruction interface of the preclinical high-resolution micro-CT scanner, which is manufactured by SEDECAL S.L. and commercialized worldwide.El trabajo de este proyecto se encuadra dentro de una línea de investigación que se desarrolla en el Laboratorio de Imagen Médica de la Unidad de Medicina y Cirugía Experimental (UMCE) del Hospital General Universitario Gregorio Marañón y el Departamento de Bioingeniería e Ingeniería Aeroespacial de la Universidad Carlos III de Madrid. Su objetivo es diseñar, desarrollar y evaluar nuevos sistemas de adquisición de datos, procesamiento y reconstrucción de imágenes multi-modales para aplicaciones en investigación preclínica. Dentro de esta línea de investigación se ha desarrollado un tomógrafo de rayos X de alta resolución para pequeños animales (micro-TAC add-on). Actualmente, la tomografía axial computarizada es una de las técnicas más ampliamente utilizadas para la obtención de información anatómica in vivo. Existe una serie de artefactos de distinta naturaleza en este tipo de imágenes que generalmente degradan y dificultan el análisis cualitativo y cuantitativo de las imágenes, dando lugar a una necesidad imperante de desarrollar algoritmos de corrección y/o reducción de estos artefactos. El objetivo general del presente proyecto es la implementación de un algoritmo para la corrección del artefacto de truncamiento en el escáner micro-TAC add-on desarrollado en el Hospital Universitario Gregorio Marañón. Este artefacto aparece debido a la adquisición de proyecciones incompletas cuando parte de la muestra, especialmente ratas obesas, se extiende fuera del campo de visión. Estas inconsistencias en los datos obtenidos pueden dar lugar a la aparición de bandas brillantes y errores en la cuantificación de las imágenes después del proceso de reconstrucción. En primer lugar, se ha estudiado el artefacto de truncamiento en el escáner micro-TAC add-on de alta resolución. Seguidamente, se ha llevado a cabo una revisión de los métodos propuestos en la bibliografía, seleccionando una estrategia óptima para el micro-TAC add-on bajo estudio: una técnica de extrapolación del sinograma publicado por Ohnesorge et al [1]. Este método consiste en una extrapolación de espejo simétrico de las proyecciones truncadas que garantiza la continuidad en el punto de truncamiento. Incluye el modelado de una sinusoide que asegura una caída de señal en los valores de atenuación suave. Este método ha sido validado en estudios simulados y reales. Los resultados muestran una clara reducción del artefacto de truncamiento. El resultado de este proyecto ha sido incorporado en la interfaz de reconstrucción del escáner pre-clínico micro-TAC add-on de alta resolución fabricado por SEDECAL S.A. y comercializado por todo el mundo.Ingeniería Biomédic

Development of data acquisition software for X-ray radiography, computed tomography, and stereography of multiphase flow

Multiphase flows are incredibly complex systems of which we know only the basics. These flows are common in a variety of industrial processes such as oil pipelines, biochemical reactions, and food production. Due to the large array of areas affected by multiphase flow, understanding and modeling the hydrodynamics of these systems is paramount to economic success in the industrial world. As a result, to more fully understand multiphase flow, a method for noninvasively investigating and measuring process parameters must be created. This study will develop control software for a system capable of acquiring data for creating X-ray projection images, computed tomography, and stereography. The system development, software development, hardware integration, algorithm refinement, and system demonstrations will be presented

Medium resolution Computed Tomography through phosphor screen detector and 3D image analysis

Computed Tomography (CT) technology allows the cross sectional imaging of objects nondestructively and is of great importance because of its capability of detecting interior defects. CT technology is especially widely used in the areas of material industries, airspace industries and medical diagnostics. However this detail of information comes at a price. Modern CT data acquisition systems collect huge amounts of data making the processing of that data a significant challenge. In order to deal with continuing demand of large object 3D CT technology and increased 3D CT data size we have developed a large field of view 3D CT scan capability addressing the required resolution (100 [Mu]) and handling the data acquisition, transfer, processing, viewing and information extraction. The new phosphor screen detector employing CCD camera with approximately 44cm x 30cm active imaging area and 3073 x 2048 pixel size, scans large objects at medium resolution. Phosphor screen computed tomography system control software developed in this thesis integrates image acquisition, image calibration, motion control and CT Scan. CT data generated as a result of a scan requires a 3D visualization tool to fulfill goal of inspection and analysis of object. The 3D visualization tool designed at Center of Non Destructive Evaluation employs ray cast volume rendering method to visualize volume CT data on PC. While the ability to get an overview of these large 3D CT data sets (3GB) is powerful, the lack of tools to extract information from this qualitative display limits the 3D CT capability. This research has added another tool to the existing software that will be used to identify and separate features in a sample based on identifying neighbor approach. Algorithms for image analysis and processing like percentage porosity analysis and correction of rogue/bad pixels are also part of the research. The result in dealing with the data acquisition and data manipulation issues is a significant extension of 3D CT imaging capabilities