X-ray image quality and display- contrast, resolution, noise Flashcards
How can subject contrast be increased?
Subject contrast can be increased by:
Lowering X-ray beam energy
reducing kVp & filtration
this results in higher patient dose compared to a higher kV and lower filtration achieving the same detector dose
Reducing the effect of scatter
Subject contrast: Increasing the X-ray beam energy by increasing kV will:
reduce subject contrast
reduce the patient dose considerably (if the same dose to the detector is achieved compared to lower kV and reduced filtration)
increase the effect of scatter
this may be reduced using anti-scatter measures
Lost contrast could be partly recovered using digital image processing
What can scatter depend on?
Scatter depends on
X-ray beam energy
image field size
thickness of irradiated area
It is produced in the patient via Compton scattering
Scatter reduces subject contrast
How can scatter be reduced?
Scatter can be reduced using
A grid
An air gap (not covered)
Reducing the thickness of material – for example by compressing the breast during a mammogram
Reducing the area irradiated using collimation
Scatter Reduction Grids
A grid is a device which is placed between the patient and the image receptor
Its purpose is to
transmit as many useful (primary) image forming X-ray photons as possible
reject (absorb) as many scattered (secondary) X-ray photons as possible – leading to better contrast
A grid is generally recommended for
field sizes > 10 cm2
high kVp (though still used for low kVp techniques e.g. mammography)
soft tissue structures
Grids do not eliminate all the scattered X-ray photons
Grids do not transmit all the primary X-ray photons so the exposure must be increased to compensate
Grids increase patient dose
Grids improve subject contrast
Contrast & X-ray Detectors
The detection and subsequent display of radiographic image contrast is dependent on
the contrast resolution of the detector which in turn depends on the bit depth
bit depth – how many levels of grey that can be represented by the detector
The detection system must be able to accurately represent the subject contrast available in the latent image
Low bit-depth leads to quantization errors – a discrepancy between the true value of the detector pixel signal and that represented by the digital value resulting from the ADC
These errors can lead to contouring in smooth structures and added image noise
Generally, 10 or 12-bit images are used in radiography
Window & Level
Reducing the window width
Increases the contrast of the structures that have detector pixel values within the window
Reduces the range of detector pixel values displayed on the image
Changing the level moves the window left and right to select a different range of detector pixel values.
Image Resolution
Detail
Unsharpness
Blurring
Spatial Resolution
Display Contrast
Displayed contrast depends on many factors including:
image processing applied prior to display
the quality of the display monitor
maximum brightness
number of grey levels available
calibration of the monitor
use of a suitable display curve relating digital values to grey level
Geometric Unsharpness Key Points
Geometric unsharpness results from having a finite sized X-ray tube focus
Geometric unsharpness imposes a limitation on the imaging system in being able to resolve fine details
X-ray Image Quality & Display
Sources of image unsharpness
Geometric
Detector layer
Pixel size unsharpness
Movement unsharpness
Geometric unsharpness can be reduced by:
Reducing the object to detector distance
Increasing the focus to object distance
Reducing the focal spot size
Detector Layer Unsharpness
Light scatter in phosphor-based detectors is a source of image unsharpness
Generally, the thicker the phosphor the more unsharpness produced
Decreasing the thickness of the detection layer increases the resolution, but decreases the absorption efficiency resulting in more image noise
The noise can be reduced by increasing the exposure, however this will lead to an increase in patient dose
Detector Pixel Unsharpness: what is pixel pitch
Pixel pitch is the distance between the centre of two adjacent pixels (aka pixel size)
Reducing the pixel pitch could allow smaller objects to be discriminated in the image
The pixel pitch sets the upper limit for the spatial resolution of the X-ray imaging system
Detector Pixel Unsharpness: What happens if you reduce the pixel pitch?
Reducing the pixel pitch of the X-ray detector will generally increase the resolution of the final image only if the fine details in the latent image have not already been lost by detection layer blurring
Reducing the pixel pitch of the X-ray detector requires that the exposure is increased to compensate for the loss of area in order to produce the same signal level from the pixel – this will increase dose to the patient
Data handling and storage requirements will be increased with smaller detector pixel sizes for the same area of coverage
Movement Unsharpness
Caused by movement of anatomy during the exposure relative to the source and detector
Minimized by
reducing exposure time (this may impact focal spot selection and increase geometric blurring
getting the patient to hold their breath
immobilizing the patient
Resolution Test Objects
Typical resolution test pattern
Groups of lines etched in lead and encased in a plastic support
Each group is made up of equally spaced equal width lines of lead and air
The (spatial) frequency of each group is different
The spatial frequency is quoted in line pairs per mm: LP/mm
For the pattern shown the spatial frequency extends from 0.1 – 4.88 LP/mm
When imaged on a practical X-ray imaging system only so many patterns can be seen on the final image. The highest number of line pairs per mm that can be seen is called the limiting resolution which gives an indication of the spatial resolution performance of the imaging system
What is Image noise?
superimposes a random pattern over the image
if strong enough this pattern can obscure anatomical details such that features may be undetectable
