Computer Tomography (CT) imaging was invented in 1972 by Godfrey Hounsfield. It is a powerful NDT technique that uses a computer to produce 2-D cross-sectional and 3-D images of an object from X-radiographs. Characteristics of the internal structure of an object such as dimensions, shape, internal defects, and density are readily available from CT images.

The technique of tomography involves passing a series of X-rays through an object, and measuring the change in intensity or attenuation of these X-rays by placing a series of detectors on the opposite side of the object from the X-ray source. The measurements of X-ray attenuation are called projections and are collected at a variety of angles.

Each of these attenuation measurements are then digitised and stored in a computer where a specialised algorithm is used to reconstruct the distribution of X-ray attenuation to produce a 2D cross sectional image. So X-ray attenuation ( ) basically corresponds to the grey levels in a CT slice, and reflects the proportion of X-rays scattered or absorbed as they pass through each voxel (volumetric pixel - a point in a regular grid in 3 dimensional space). If this process is repeated at various heights along the object, we obtain a series of 2D cross-sectional CT images, which can then be stacked on top of each other to obtain the 3D volume image.









The 3 phases of CT Image Reconstruction

(1) Scan Phase

CT machines use various methods of acquiring the necessary projection data to produce a CT image. These methods are classified in terms of their scan geometry about the object.



For example, in medicine, 2^nd generation CT systems are generally used which operate a translate/rotate scan geometry about the object, whereas most industrial systems use a 3^rd generation configuration involves the use of cone beam projections and the object under study being placed on a rotating manipulator. This enables the system to collect the many angles of X-ray attenuation data or X-ray projections needed to perform CT reconstruction.

(2) Image Reconstruction

In this phase specialised algorithms are used to reconstruct a 2D image from the set of X-ray projections, known as the sinogram, produced during the scan phase. In other words, complicated algorithms are used to reconstruct the distribution of the X-ray attenuation data to produce a digital image.

The most common algorithm used for this process is the Filtered Back Projection method, which calculates from this set of 1D sinogram lines a reconstructed 2D image.

Back projection is the mathematical process of obtaining the digital image from the projection data or sinogram, but if it is not filtered in some way, results in a very noisy image, hence the use of Filtered Back Projection

The CT image is now digital in the form of a matrix of pixels, and a part of the reconstruction process is the calculation of CT numbers for each image pixel

The CT numbers are calculated from the X-ray attenuation data for each individual voxel first calculated in the reconstruction process.



X-ray attenuation ( ) depends on both the density and atomic number (Z) of materials and the energy of the X-ray photons. Therefore, the density of the materials determines the CT numbers. So for all practical purposes, the CT image is an image of the densities of the material.

(3) Visible Image Formation

In this phase the digital image, consisting of a matrix of pixels with each pixel having an assigned CT number is converted into a visible image represented by different shades of grey. Each number represents a shade of grey with +1000 (white) and -1000 (black) at either end of the spectrum.

Image Quality

As with any radiographic technique image quality is an important concern, as the ability to reliably detect defects and structural irregularities within the component depends on the quality of the image produced.

The main parameters used when considering image quality are highlighted below:

• Image contrast - This is the ability of an imaging procedure to reliably depict very subtle differences in contrast.
• Spatial resolution - This is the ability to discriminate between adjacent objects and is a function of pixel size
• Noise - Image noise is mainly caused by the quantum structure of the X-ray beam and is an important determinant of CT image quality as it limits the visibility of low-contrast structures.
• Artefacts - The appearance of details in the CT image not present in the scanned object.

Advantages and Disadvantages of CT Technique

The main advantage of CT is that it provides (in a non-destructive way) quantitative information on the density and geometry of an object from 2D cross sectional images.

CT holds many advantages over conventional film; firstly it completely eliminates the superimposition of images of structures outside the area of interest. Secondly, because of the inherent high-contrast resolution of CT, differences between materials that vary in physical density by less than 1% can be distinguished. This excellent density sensitivity allows CT to be able to highlight structural irregularities.

Furthermore, because CT images are digital, they may be enhanced, analysed, compressed, archived, and the digital data can be used in performance calculations which enables comparisons with other NDT techniques.

However, CT also has limitations, the most fundamental of which is that objects under examination must be small enough to be accommodated by the CT equipment available to the user and can be fully penetrated by the X-ray energies used by that particular system. Also, CT reconstruction algorithms require that a full 180 degrees of data be collected by the scanner.

Another potential drawback with CT imaging is the possibility of artefacts in the data, which limit a user's ability to quantitatively extract density, dimensional, or other data from an image. Therefore, as with any technique, the user must learn to recognise and be able to disregard common artefacts.

Final Comment

Computed tomography is a radiographic method that provides an ideal examination technique whenever the primary goal is to locate and size planar and volumetric detail in three dimensions. Because of the good penetrability of X-rays, CT permits the non-destructive physical characterisation of the internal structure of materials. Also, since the method is X-ray based, it applies equally well to metallic and non-metallic specimens, solid and fibrous materials, and smooth and irregular surfaced objects. Furthermore, the ability of a CT system to image thin cross sectional areas of interest through an object, means CT data can provide evaluations of material integrity that cannot currently be provided non-destructively by any other means.