X-ray Computed Tomography (CT)
What is X-ray Computed Tomography (CT)
The gray levels in a CT slice image correspond to X-ray attenuation, which reflects the proportion of X-rays scattered or absorbed as they pass through each voxel. X-ray attenuation is primarily a function of X-ray energy and the density and composition of the material being imaged.
Fundamental Principles of X-ray Computed Tomography (CT)
In general for geological materials, the photoelectric effect is the dominant attenuation mechanism at low X-ray energies, up to approximately 100-150 keV, after which Compton scatter predominates. The practical importance of this transition is that the photoelectric effect is proportional to atomic number Z4-5, whereas Compton scattering is proportional only to Z, or, to first order, mass density. As a result, low-energy X-rays are more sensitive to differences in composition than high-energy ones, but are also attenuated much more quickly, limiting the thickness of high-density material that can be penetrated and imaged with them.
The figure on the right shows linear attenuation coefficients as a function of energy for four minerals: quartz, orthoclase, calcite, and almandine garnet. Quartz and orthoclase are very similar in mass density (2.65 g/cm3 vs. 2.59 g/cm3), but at low energy their attenuation coefficients are different because of the presence of relatively high-Z potassium in the feldspar. With rising X-ray energy, their attenuation coefficients converge, and at approximately 125 keV they cross; above ~125 keV quartz is slightly more attenuating, owing to its higher density. Thus, these two minerals can be differentiated in CT imagery if the mean X-ray energy used is low enough, but at higher energies they are nearly indistinguishable. Calcite, though only slightly more dense (2.71 g/cm3) than quartz and orthoclase, is substantially more attenuating at low energy, owing to the presence of calcium. Here the divergence with quartz persists to slightly higher energies, indicating that it should be possible to distinguish the two even in higher-energy scans. High-density, high-Z phases such as almandine are distinguishable at all energies from the other rock-forming minerals examined here.
This principle is illustrated in the image at right and an animation that can be viewed by clicking on the link below. A hand sample of garnet-biotite-kyanite schist (top left) is rotated, and its midsection is imaged with a planar fan beam (blue). The attenuation of X-rays by the sample as it rotates is shown in the upper right; the more attenuation there is along a beam path leading from the point source (bottom) to the linear detector (top), the fewer X-rays reach the detector. The data collected at each angle are compiled in the bottom right. In this image the horizontal axis corresponds to detector channel, and the vertical axis corresponds to rotation angle (or time), and brightness corresponds to the extent of X-ray attenuation. The resulting image is called a sinogram, as any point in the original object corresponds to a sine curve. After data acquisition is complete, reconstruction begins. Each row of the sinogram is first convolved with a filter, and projected across the pixel matrix (bottom right) along the angle at which it was acquired. Once all angles have been processed, the image is complete.
Animation of CT reconstruction ( 9.1MB Mar30 07)
X-ray Computed Tomography (CT) Instrumentation - How Does It Work?
The great majority of CT systems use X-ray tubes, although tomography can also be done using a synchrotron or gamma-ray emitter as a monochromatic X-ray source. Important tube characteristics are the target material and peak X-ray energy, which determine the X-ray spectrum that is generated; current, which determines X-ray intensity; and the focal spot size, which impacts spatial resolution.
Most CT X-ray detectors utilize scintillators. Important parameters are scintillator material, size and geometry, and the means by which scintillation events are detected and counted. In general, smaller detectors provide better image resolution, but reduced count rates because of their reduced area compared to larger ones. To compensate, longer acquisition times are used to reduce noise levels. Common scintillation materials are cesium iodide, gadolinium oxysulfide, and sodium metatungstate.
In cone-beam scanning, the linear array is replaced by a planar detector, and the beam is no longer collimated. Data for an entire object, or a considerable thickness of it, can be acquired in a single rotation. The data are reconstructed into images using a cone-beam algorithm. In general, cone-beam data are subject to some blurring and distortion the further one goes from the central plane that would correspond to single-slice acquisition. They are also more subject to artifacts stemming from scattering if high-energy X-rays are utilized. However, the advantage of obtaining data for hundreds or thousands of slices at a time is considerable, as more acquisition time can be spent at each turntable position, decreasing image noise.
Parallel-beam scanning is done using a specially configured synchrotron beam line as the X-ray source. In this case, volumetric data are acquired and there is no distortion. However, the object size is limited by the width of the X-ray beam; depending on beam line configuration, objects up to 6 cm in diameter may be imaged. Synchrotron radiation generally has very high intensity, allowing data to be acquired quickly, but the X-rays are generally low-energy (< 35 keV), which can preclude imaging samples with extensive high-Z materials.
Other variants are multiple-slice acquisition, in which a planar detector is used but data are processed with a fan-beam reconstruction algorithm, and spiral scanning, in which sample elevation is changed during data acquisition, potentially reducing cone-beam artifacts.
- Measuring 3D size and spatial distribution of crystals, clasts, vesicles, etc.
- Nondestructive volumetric study of rare specimens (fossils, meteorites, etc.)
- 3D measurement of fluid flow fields, including porosity, microporosity, and fracture extent and roughness
- 3D fabric determination (foliations, shape preferred orientations, network properties)
- Inspection and measurement of morphology in fossils and Recent biological specimens
- Detection and examination of high-density economic trace phases
- Reconnaissance imaging of samples for optimal geochemical exploitation (for example, locating crystal central sections, spiral axes, solid and fluid inclusions).
Strengths and Limitations of X-ray Computed Tomography (CT)?
- Entirely non-destructive 3D imaging
- Little or no sample preparation required
- Reconstruction is generally attenuation-conservative, allowing sub-voxel level details to be extracted.
- Resolution limited to about 1000-2000x the object cross-section diameter; high resolution requires small objects
- Finite resolution causes some blurring of material boundaries
- Calibration of gray levels to attenuation coefficients complicated by polychromatic X-rays
- Large (dm-scale) geological specimens cannot be penetrated by low-energy X-rays, reducing resolving capability
- Not all features have sufficiently large attenuation contrasts for useful imaging (carbonate fossils in carbonate matrix; quartz vs. plagioclase)
- Image artifacts (beam hardening) can complicate data acquisition and interpretation
- Large data volumes (gigabytes+) can require considerable computer resources for visualization and analysis
User's Guide - Sample Collection and Preparation
Data Collection, Results and Presentation
The two standard modes of 3D visualization are volume rendering and isosurfacing. Volume rendering consists of mapping each CT value to a color and an opacity. Thus, some phases can be rendered transparent, allowing internal features to be revealed. Isosurfacing involves defining 3D contour surfaces that delineate boundaries between CT numbers, much as contour lines separate elevations values on a topo map.
Because CT data sets typically comprise hundreds of images and thousands of megabytes, they are not amenable to traditional publishing. However, CT data and visualizations are increasingly being served over the world wide web. An example is the Library of Digital Morphology (more info) website.
The following literature can be used to further explore X-ray Computed Tomography (CT)
- ASTM, 1992, Standard Guide for Computed Tomography (CT) Imaging, ASTM Designation E 1441 - 92a. In: 1992 Annual Book of ASTM Standards, Section 3 Metals Test Methods and Analytical Procedures. ASTM, Philadelphia, pp. 690-713.
- Ketcham, R.A. and Carlson, W.D., 2001, Acquisition, optimization and interpretation of X-ray computed tomographic imagery: Applications to the geosciences. Computers and Geosciences, 27, 381-400.
For more information about X-ray Computed Tomography (CT) follow the links below.
Teaching Activities and Resources
Teaching activities, labs, and resources pertaining to X-ray Computed Tomography (CT).