Quasi-Exact Helical Cone Beam Reconstruction for Micro CT

A cone beam micro-CT system is set up to collect truncated helical cone beam data. This system includes a micro-focal X-ray source, a precision computer-controlled X-Y-Z-theta stage, and an image-intensifier coupled to a large format CCD detector. The helical scanning mode is implemented by rotating and translating the stage while keeping X-ray source and detector stationary. A chunk of bone and a mouse leg are scanned and quasi-exact reconstruction is performed using the approach proposed in J. Hu et al. (2001). This approach introduced the original idea of accessory paths with upper and lower virtual detectors having infinite axial extent. It has a filtered backprojection structure which is desirable in practice and possesses the advantages of being simple to implement and computationally efficient compared to other quasi-exact helical cone beam algorithms for the long object problem

Automatic alignment for three-dimensional tomographic reconstruction

In tomographic reconstruction, the goal is to reconstruct an unknown object from a collection of line integrals. Given a complete sampling of such line integrals for various angles and directions, explicit inverse formulas exist to reconstruct the object. Given noisy and incomplete measurements, the inverse problem is typically solved through a regularized least-squares approach. A challenge for both approaches is that in practice the exact directions and offsets of the x-rays are only known approximately due to, e.g. calibration errors. Such errors lead to artifacts in the reconstructed image. In the case of sufficient sampling and geometrically simple misalignment, the measurements can be corrected by exploiting so-called consistency conditions. In other cases, such conditions may not apply and we have to solve an additional inverse problem to retrieve the angles and shifts. In this paper we propose a general algorithmic framework for retrieving these parameters in conjunction with an algebraic reconstruction technique. The proposed approach is illustrated by numerical examples for both simulated data and an electron tomography dataset

A multi-resolution image reconstruction method in X-ray computed tomography

International audienceWe propose a multiresolution X-ray imaging method designed for non-destructive testing/ evaluation (NDT/NDE) applications which can also be used for small animal imaging studies. Two sets of projections taken at different magnifications are combined and a multiresolution image is reconstructed. A geometrical relation is introduced in order to combine properly the two sets of data and the processing using wavelet transforms is described. The accuracy of the reconstruction procedure is verified through a comparison to the standard filtered backprojection (FBP) algorithm on simulated data

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

A General Local Reconstruction Approach Based on a Truncated Hilbert Transform

Exact image reconstruction from limited projection data has been a central topic in the computed tomography (CT) field. In this paper, we present a general region-of-interest/volume-of-interest (ROI/VOI) reconstruction approach using a truly truncated Hilbert transform on a line-segment inside a compactly supported object aided by partial knowledge on one or both neighboring intervals of that segment. Our approach and associated new data sufficient condition allows the most flexible ROI/VOI image reconstruction from the minimum account of data in both the fan-beam and cone-beam geometry. We also report primary numerical simulation results to demonstrate the correctness and merits of our finding. Our work has major theoretical potentials and innovative practical applications