Image formation and display

Once X-rays are detected and converted into electrical signals, these signals must be sampled, digitised, and processed to create the image displayed on a monitor.

From Analogue Signal to Digital Image

The electrical signals generated by each detector element are analogue, meaning continuous values representing X-ray intensity.

To store and manipulate them digitally, the signals undergo two key processes:

1. Sampling – dividing the image into discrete pixels.
2. Quantisation – assigning a discrete numerical value (and ultimately grey level) to each pixel based on signal intensity.

The result is a digital image matrix that can be processed, transmitted, and displayed without loss of fidelity.

Image Matrix and Pixel Size

Image Matrix

• A digital image consists of a matrix of small square elements called pixels (picture elements).
• Typical matrix sizes: 1024 × 1024, 2048 × 2048, or higher.
• Each pixel represents a tiny area of the patient and contains one grey-level value corresponding to the detected X-ray intensity.

Pixel Size

Pixel size = Field of View (FOV) / Matrix Dimension

• Smaller pixels → higher spatial resolution, but increased noise (each pixel receives fewer photons).
• Pixel size is directly related to detector element pitch (typically 100–200 μm in DR).

Sampling Frequency and the Nyquist Limit

To accurately represent fine detail, the sampling frequency must satisfy the Nyquist criterion:

f_s ≥ 2f_max

Where:

• f_s​ = sampling frequency,
• f_max​ = highest spatial frequency in the image.

If the sampling frequency is too low, aliasing occurs. When this happens, high-frequency details appear as false patterns or moiré artefacts. Digital systems therefore limit or filter high-frequency content before sampling to prevent aliasing.

When we talk about sampling frequency, we’re referring to how rapidly the analogue signal is measured as the signal is being read out/digitised.

Bit Depth and Grey Levels

After sampling, each pixel’s signal intensity (which represents the detected X-ray exposure at that location) must be assigned a numerical value.

This process is called quantisation, and it converts the continuous analogue signal into discrete digital levels.

Bit Depth

• Bit depth (n) refers to the number of bits used to store the intensity value for each pixel.
• The bit depth determines how many distinct grey levels the system can represent.

Number of available grey levels = 2ⁿ

Bit Depth	Number of Grey Levels	Typical Use
8-bit	256	Display monitors
10-bit	1024	Computed radiography
12–16-bit	4096–65 536	DR, CT, mammography

Relationship Between Signal and Grey Level

The bit depth simply defines how finely those signal values can be divided. In other words, the precision of the digital representation.

The actual grey level assigned to a pixel depends on the magnitude of the sampled detector signal (i.e. how much X-ray exposure that pixel received).

If the detector signal represents brightness on a continuous scale, bit depth defines how many “steps” that brightness scale is divided into. More bits → more steps → smoother tonal transitions and greater contrast resolution.

Window Width and Window Level

Definitions

• Window width (WW): range of pixel values displayed across the available grey scale → controls contrast.
• Window level (WL): central value of the window → controls brightness.

Think of each pixel as having a numerical value that represents the detected X-ray intensity (exposure) at that point. We can’t look at an array of numerical values and interpret it as an image with our naked eye. These numerical values ned to get assigned a greyscale in order to create an image.

The assigning of grey values to numerical values is called windowing.

The window width determines which range of numerical values will be assigned a grey value. Values above this range appear white; values below it appear black. Subtle differences in tissue attenuation outside the selected window are therefore not visible.

The window level defines the numerical value to which the central grey value will be assigned. This effectively sets the brightness of the image.

The number of potential different grey values available is determined by the bit depth. A higher bit depth allows finer gradations between pixel values and therefore better contrast resolution.

Key Takeaways and Exam Tips:

• Sampling divides the detector signal into pixels; quantisation assigns numerical values.
• Pixel size and sampling frequency determine spatial resolution.
• Bit depth determines contrast resolution.
• Dynamic range is much wider in digital systems. Meaning a higher range of detector exposures can generate a usable image.
• Window width and level control the displayed contrast and brightness.
• Common exam question: “Define bit depth, window width, and window level, and explain how they affect image display.”

Up Next

Next, we’ll move on to Fluoroscopy and Real-Time Imaging, where we’ll explore the physics of continuous X-ray imaging. This includes image intensifiers, flat-panel fluoroscopy detectors, and methods to minimise dose while maintaining real-time performance.