It’s easy to have a doctor look at an image and decide if it’s good or bad. When you need to figure out why and how to improve it, you need to look at “good” and “bad” in more detail. There are seven measurements, from simple to complex, used by engineers to look at the quality of images and the detectors that produce them.
Resolution
Resolution is the smallest space between two objects that can be imaged clearly. It specifies the resolution of an imaging system quantitatively in terms of its Point Spread Function (PSF), which is the image of an ideal point object. When the resolution is low, it’s not clear where one object begins and another ends.
Contrast
Contrast is a measure of difference between regions in an image. In a high contrast image, small changes in the density or thickness of bone and flesh are obvious. When contrast is low, small differences are hard to see or completely undetectable. Contrast depends on several different factors. In designing a system, contrast will be affected by the type of device used to record the image (film, CR plate, or various digital detectors), the energy spectrum of the x-ray beam, whether or not scatter radiation is present in the x-ray beam, and whether some other baseline signal is present in the imaging device. A high contrast system will have a tight spectrum x-ray beam, a grid to remove scattered radiation, and a low level of baseline exposure (film) or signal (digital detectors).
Noise
Noise is the uncertainty in a signal due to random fluctuations in that signal. There are many causes for these fluctuations, including quantum noise, electronic noise, fixed pattern noise and others. Different types of noise will look different in an image, but all have the effect of making it harder to see the real picture. The classic example of noise is static in an analog television signal.
Modulation Transfer Function (MTF)
Modulation Transfer Function (MTF) is the spatial frequency response of an imaging system. The MTF is a measurement of how much the contrast of an image drops as the objects you are looking at get smaller. It is a result of the resolution and noise of the system.
Signal-to-Noise Ratio (SNR)
How much image (signal) you see compared to the noise in the image. It is measured as the signal amplitude divided by noise amplitude. SNR can be improved in digital systems by increasing exposure (signal), and this is a common cause of overexposure in radiography systems with excessive electronic noise or radiation scattering.
Noise Power Spectrum (NPS)
The Wiener Spectrum (or Noise Power Spectrum, NPS) is the noise amplitude as a function of spatial frequency, similar to MTF. It combines the average size, separation, and intensity of noise in the image into a single number. Calculation of the NPS is done by taking the Fourier Transform of the auto-correlation function in a uniformly exposed radiographic image.
Detective Quantum Efficiency (DQE)
The Detective Quantum Efficiency (DQE) is an important characteristic in how the imaging system affects the SNR. It is designed as the ratio between SNR out2 (the signal/noise ratio of the image created by the detector) and the SNR in2 (the theoretical signal/noise ratio of the x-ray image reaching the detector). A perfect imaging system in terms of noise performance has a DQE of 1, preserving the SNR of all signals it receives.
