X-ray absorption imaging is used in the medical field since a long time, but recent advance in phase-contrast imaging made it feasible in a clinical setup. X-ray Phase-contrast imaging technique using a Hartmann sensor allows extracting the absorption and phase information in a single acquisition, allowing to extract a phase-shift information with a minimal exposition and deposited dose. An iterative wavefront reconstruction (IR-WF) algorithm is necessary to extract the phase and absorption values from an acquired image. Our method consists of merging the wavefront reconstruction with a computed tomographic iterative reconstruction (IR-CT) to ensure that all images converge to the same result, improving the final 3D volume.
sequences. Sizing, surface and volume rendering can be extracted and compared with targeted dimensions. In this work, we use millimeter wave systems tomographic system (100 and 300 GHz), frequency modulated systems (100 and 300 GHz), and pulse time domain systems (100 GHz to 4 THz) for non destructive characterization of 3D printed additive manufacturing parts. The aim of this talk to to show the advantages and disadvantages of several techniques to define their application aera. This work is associated to a data processing analysis using automated segmentation, extracting of the different volumes of interest (VOI) composing the sample. A mesh is performed for each VOI to numerically calculate the dimensions, surfaces and volume which leads to 3D visualization and dimensional measurements. Overall sequence is implemented onto unique software and validated through different sample analysis.
In the context of large-angle cone-beam tomography (CBCT), we present a practical iterative reconstruction (IR) scheme designed for rapid convergence as required for large datasets. The robustness of the reconstruction is provided by the “space-filling” source trajectory along which the experimental data is collected. The speed of convergence is achieved by leveraging the highly isotropic nature of this trajectory to design an approximate deconvolution filter that serves as a pre-conditioner in a multi-grid scheme. We demonstrate this IR scheme for CBCT and compare convergence to that of more traditional techniques.
Achieving sub-micron resolution in lab-based micro-tomography is challenging due to the geometric instability of the imaging hardware (spot drift, stage precision, sample motion). These instabilities manifest themselves as a distortion or motion of the radiographs relative to the expected system geometry. When the hardware instabilities are small (several microns of absolute motion), the radiograph distortions are well approximated by shift and magnification of the image. In this paper we examine the use of re-projection alignment (RA) to estimate per-radiograph motions. Our simulation results evaluate how the convergence properties of RA vary with: motion-type (smooth versus random), trajectory (helical versus space-filling) and resolution. We demonstrate that RA convergence rate and accuracy, for the space-filling trajectory, is invariant with regard to the motion-type. In addition, for the space-filling trajectory, the per-projection motions can be estimated to less than 0.25 pixel mean absolute error by performing a single quarter-resolution RA iteration followed by a single half-resolution RA iteration. The direct impact is that, for the space-filling trajectory, we need only perform one RA iteration per resolution in our iterative multi-grid reconstruction (IMGR).We also give examples of the effectiveness of RA motion correction method applied to real double-helix and space-filling trajectory micro-CT data. For double-helix Katsevich filtered-back-projection reconstruction (≈2500x2500x5000 voxels), we use a multi-resolution RA method as a pre-processing step. For the space-filling iterative reconstruction (≈2000x2000x5400 voxels), RA is applied during the IMGR iterations.
The Mojette transform is a discrete and exact Radon transform, based on the discrete geometry of the projection
and reconstruction lattice. The specific sampling scheme of the Mojette transform results in theoretical exact
image reconstruction. In this paper, we compare the reconstructions obtained with the Mojette transform to
the ones obtained with several usual projection/backprojection digitized Radon transform. These experiments
validate and demonstrate the performance of the Mojette transform sampling over classical implementations
based on continuous space.
Trabecular bone and its micro-architecture are of prime importance for health. Changes of bone micro-architecture are linked to different pathological situations like osteoporosis and begin now to be understood. In a previous paper, we started to investigate the relationships between bone and vessels and we also proposed to build a Bone Atlas. This study describes how to proceed for the elaboration and use of such an atlas. Here, we restricted the Atlas to legs (tibia, femur) of rats in order to work with well known geometry of the bone micro-architecture. From only 6 acquired bone, 132 trabecular bone volumes were generated using simple mathematical morphology tools. The variety and veracity of the created micro-architecture volumes is presented in this paper. Medical application and final goal would be to determinate bone micro-architecture with some angulated radiographs (3 or 4) and to easily diagnose the bone status (healthy, pathological or healing bone...).
In this paper we present an innovative data and image processing sequence to perform non-destructive inspection from 3D terahertz (THz) images. We develop all the steps starting from a 3D tomographic reconstruction of a sample from its radiographs acquired with a monochromatic millimetre wave imaging system. Thus an automated segmentation provides the different volumes of interest (VOI) composing the sample. Then a 3D visualization and dimensional measurements are performed on these VOI, separately, in order to provide an accurate nondestructive testing (NDT) of the studied sample. This sequence is implemented onto an unique software and validated through the analysis of different objects
We address several acquisition questions that have arisen for the high cone-angle helical-scanning micro-CT facility developed at the Australian National University. These challenges are generally known in medical and industrial cone-beam scanners but can be neglected in these systems. For our large datasets, with more than 20483 voxels, minimising the number of operations (or iterations) is crucial. Large cone-angles enable high signal-to-noise ratio imaging and a large helical pitch to be used. This introduces two challenges: (i) non-uniform resolution throughout the reconstruction, (ii) over-scan beyond the region-of-interest significantly increases re- quired reconstructed volume size. Challenge (i) can be addressed by using a double-helix or lower pitch helix but both solutions slow down iterations. Challenge (ii) can also be improved by using a lower pitch helix but results in more projections slowing down iterations. This may be overcome using less projections per revolution but leads to more iterations required. Here we assume a given total time for acquisition and a given reconstruction technique (SART) and seek to identify the optimal trajectory and number of projections per revolution in order to produce the best tomogram, minimise reconstruction time required, and minimise memory requirements.
In this paper, we develop a dual-energy ordered subsets convex method for transmission tomography based on material matching with a material dictionary. This reconstruction includes a constrained update forcing material characteristics of reconstructed atomic number (Z) and density (p) volumes to follow a distribution according to the material database provided. We also propose a probabilistic classification technique in order to manage this material distribution. The overall process produces a chemically segmented volume data and outperforms sequential labelling computed after tomographic reconstruction.
KEYWORDS: Radiography, Sensors, X-rays, Convolution, Signal to noise ratio, X-ray sources, 3D modeling, Data modeling, X-ray imaging, Signal attenuation
Micro scale computed tomography (CT) can resolve many features in cellular structures, bone formations, minerals properties and composite materials not seen at lower spatial-resolution. Those features enable us to build a more comprehensive model for the object of interest. CT resolution is limited by a fundamental trade off between source size and signal-to-noise ratio (SNR) for a given acquisition time. There is a limit on the X-ray flux that can be emitted from a certain source size, and fewer photons cause a lower SNR. A large source size creates penumbral blurring in the radiograph, limiting the effective spatial-resolution in the reconstruction.
High cone-angle CT improves SNR by increasing the X-ray solid angle that passes through the sample. In the high cone-angle regime current source deblurring methods break down due to incomplete modelling of the physical process. This paper presents high cone-angle source de-blurring models. We implement these models using a novel multi-slice Richardson-Lucy (M-RL) and 3D Conjugate Gradient deconvolution on experimental high cone-angle data to improve the spatial-resolution of the reconstructed volume. In M-RL, we slice the back projection volume into subsets which can be considered to have a relative uniform convolution kernel. We compare these results to those obtained from standard reconstruction techniques and current source deblurring methods (i.e. 2D Richardson-Lucy in the radiograph and the volume respectively).
Direct study of pore-scale fluid displacements, and other dynamic (i.e. time-dependent) processes is not feasible with conventional X-ray micro computed tomography (μCT). We have previously verified that a priori knowledge of the underlying physics can be used to conduct high-resolution, time-resolved imaging of continuous, complex processes, at existing X-ray μCT facilities. In this paper we present a maximum a posteriori (MAP) model of the dynamic tomography problem, which allows us to easily adapt and generalise our previous dynamic μCT approach to systems with more complex underlying physics.
Terahertz (THz) tomography is a recently developed imaging technique allowing 3D inspection of opaque objects.
In this paper, we develop an ordered subsets convex algorithm for THz transmission tomography (THz-OSC).
Since the reconstruction quality is highly depending on the THz beam energy, we investigate afterwards a multienergy
version of the algorithm in order to provide a more accurate reconstruction of the acquired sample. This
multi-energy approach is validated by reconstructing data from tomographic acquisitions measured with a 84/287
GHz transmission scanner. Then we discuss how this dual-energy approach could be able to extract physical
properties of acquired samples in addition to improving 3D reconstruction.
Micro-CT represents a modality where the quality of CT reconstruction is very high thanks to the acquisition properties.
The goal of this paper is to challenge our proposed Mojette discrete reconstruction scheme from real micro-CT data. A
first study was done to analyze bone image degradations by lowering the number of projections. A second study analyzes
trabecular bone and vessels tree through an animal study. Small vessels are filling trabecular holes with almost the same
grey levels as the bone. Therefore vessel detectability that can be achieved from the reconstruction algorithm according
to the number of projections is a major issue.
The usability of pulsed broadband terahertz radiation for the inspection of composite materials from the aeronautics industry is investigated, with the goal of developing a mobile time-domain spectroscopy system that operates in reflection geometry. A wide range of samples based on glass and carbon fiber reinforced plastics with various types of defects is examined using an imaging system; the results are evaluated both in time and frequency domain. The conductivity of carbon fibers prevents penetration of the respective samples but also allows analysis of coatings from the reflected THz pulses. Glass fiber composites are, in principle, transparent for THz radiation, but commonly with significant absorption for wavelengths >1 THz . Depending on depth, matrix material, and size, defects like foreign material inserts, delaminations, or moisture contamination can be visualized. If a defect is not too deep in the sample, its location can be correctly identified from the delay between partial reflections at the surface and the defect itself.
Three-dimensional (3-D) terahertz computed tomography has already been performed with three different reconstruction methods (standard back-projection algorithm and two iterative analyses) to reconstruct 3-D objects. A Gaussian beam model is developed according to the physical properties of terahertz waves such as the energy distribution within the propagation path. This model is included as a new convolution filter into the tomographic reconstruction methods in order to analyze the impact of a such effect and then to enhance quality and accuracy of the resulting images. We demonstrate the improvements of the optimized reconstructions for applied 3-D terahertz tomography.
The potential of terahertz technology has been clearly demonstrated by its large applications in security and defence
(remote detection of object). A flexible alternative monochromatic millimeter wave system coupled with an original
infrared temperature sensor has been developed to visualize large size 3D manufactured opaque phantoms with different
refractive index contrasts. The results clearly illustrate applied terahertz tomography particularities such as boundary
effects, refraction and diffraction losses that must be prevented for efficient inspection and detection.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.