Histogram analysis is an image processing technique commonly used to identify the edges of the image and assess the raw data prior to image display. In this method, the computer first creates a histogram of the image (Figure 7-1). A histogram is a graphic representation of a data set. A data set includes all the pixel values that represent the image before edge detection and rescaling. This graph represents the number of digital pixel values versus the relative prevalence of the pixel values in the image. The x-axis represents the amount of exposure, and the y-axis represents the incidence of pixels for each exposure level. The computer analyzes the histogram using processing algorithms and compares it with a preestablished histogram specific to the anatomic part being imaged. This process is called histogram analysis. The computer software has stored histogram models, each having a shape characteristic of the selected anatomic region and projection. These stored histogram models have values of interest (VOI), which determine the range of the histogram data set that should be included in the displayed image.

FIGURE 7-1 The histogram represents the number of digital pixel values versus the relative prevalence of those values in the latent image. The x-axis represents the amount of exposure and the y-axis the incidence of pixels for each exposure level. Each image has its own histogram.

In CR imaging, the entire imaging plate is scanned to extract the image from the photostimulable phosphor. The computer identifies the exposure field and the edges of the image, and all exposure data outside this field are excluded from the histogram. Ideally, all four edges of a collimated field are recognized. If at least three edges are not identified, all data, including raw exposure or scatter outside the field, may be included in the histogram, resulting in a histogram analysis error. Histogram analysis errors are less likely to occur with DR IRs compared with CR IRs because the image data are extracted from the exposed detectors only.

Important Relationship

Histogram Analysis

With digital systems, the computer creates a histogram of the data set. The histogram is a graph of the exposure received to the pixel elements and the prevalence of the exposures within the image. This created histogram is compared with a stored histogram model for that anatomic part; VOIs are identified, and the image is displayed.

Histogram analysis is also employed to maintain consistent image brightness despite overexposure or underexposure of the IR. This procedure is known as automatic rescaling. The computer rescales the image based on the comparison of the histograms, which is actually a process of mapping the grayscale to the VOI to present a specific display of brightness (Figure 7-2). Although automatic rescaling is a convenient feature, radiographers should be aware that rescaling errors occur for a variety of reasons and can result in poor-quality digital images.

FIGURE 7-2 Automatic rescaling is employed during histogram analysis to maintain consistent image brightness despite overexposure or underexposure of the IR.

Exposure Indicator

An important feature of digital image processing is its ability to create an image with the appropriate amount of brightness regardless of the exposure to the IR. As a result of the histogram analysis, valuable information is provided to the radiographer regarding the exposure to the digital IR. The exposure indicator provides a numeric value indicating the level of radiation exposure to the digital IR. Currently, exposure indicators are not standardized among various digital imaging equipment in use today; however, the industry is working toward standardization of the exposure indicator. See Table 7-1 for a list of CR vendor-specific exposure indicators.

TABLE 7-1

Computed Radiography Vendor-Specific Exposure Indicators

Vendor	Exposure Indicator	Value = 1 mR exposure	2× Exposure	½ Exposure
Fuji and Konica	Sensitivity (S)	200	100	400
Carestream (Kodak)	Exposure index (EI)	2000	2300	1700
Agfa	Log median value (lgM)	2.5	2.8	2.2

In CR, the exposure indicator value represents the exposure level to the imaging plate, and the values are vendor specific. Fuji and Konica use sensitivity (S) numbers, and the value is inversely related to the exposure to the plate. A 200 S number is equal to 1 mR of exposure to the plate. If the S number increases from 200 to 400, this would indicate a decrease in exposure to the IR by half. Conversely, a decrease in the S number from 200 to 100 would indicate an increase in exposure to the IR by a factor of 2, or doubling of the exposure. Carestream (Kodak) uses exposure index (EI) numbers; the value is directly related to the exposure to the plate, and the changes are logarithmic expressions. For example, a change in EI from 2000 to 2300, a difference of 300, is equal to a factor of 2 and represents twice as much exposure to the plate. Agfa uses log median (lgM) numbers; the value is directly related to exposure to the plate, and changes are also logarithmic expressions. For example, a change in lgM from 2.5 to 2.8, a change of 0.3, is equal to a factor of 2 and represents twice as much exposure to the IR. Optimal ranges of the exposure indicator values are vendor specific and vary among the types of procedures, such as abdomen and chest imaging versus extremity imaging.

DR imaging systems may also display an exposure indicator that varies according to the manufacturer’s specifications. The radiographer should monitor the exposure indicator values as a guide for proper exposure techniques. If the exposure indicator value is within the acceptable range, adjustments can be made for contrast and brightness with postprocessing functions, and this will not degrade the image. However, if the exposure is outside of the acceptable range, attempting to adjust the image data with postprocessing functions would not correct for improper receptor exposure and may result in noisy or suboptimal images that should not be submitted for interpretation.

The radiographer has a role in the selection of the appropriate anatomic part and projection before computer processing. This step indicates to the computer which histogram to use. If the radiographer selects a part other than the one imaged, a histogram analysis error may occur. In addition, any errors that occur, such as during data extraction from the IR or rescaling during computer processing, could affect the exposure indicator and provide a false value. It is important for radiographers not only to consider the exposure indicator value carefully but also to recognize its limitations.

Important Relationship

Exposure Indicators

The radiographer should strive to select techniques that result in exposure indicator values within the indicated optimum range for that digital imaging system. However, the radiographer also needs to recognize the limitations of exposure indicators in providing accurate information.

Lookup Tables

Following histogram analysis, lookup tables provide a method of altering the image to change the display of the digital image in various ways. Because digital IRs have a linear exposure response and a very large dynamic range, raw data images exhibit low contrast and must be altered to improve visibility of anatomic structures. Lookup tables provide the means to alter the brightness and grayscale of the digital image using computer algorithms. They are also sometimes used to reverse or invert image grayscale. Figure 7-3 visually compares pixel values of the original image with a processed image. If the image is not altered, the graph would be a straight line. If the original image is altered, the original pixel values would be different in the processed image and the graph would no longer be a straight line but might resemble a characteristic curve for radiographic film (Figure 7-4).

FIGURE 7-3 Straight line graph demonstrating no change in the pixel values from the original to the processed image.

For example, each pixel value could be altered to display the digital image with a change in contrast. New pixel intensities would be calculated that result in the image being displayed with higher contrast (Figure 7-5). Figure 7-6 shows the original image, the graph following changes in the pixel values, and the processed higher contrast image. Lookup tables provide a method of processing digital images in order to change the brightness and contrast displayed (Figure 7-7).

FIGURE 7-5 Lookup table altering the pixel values of a low-contrast image to display an image with higher contrast.

Important Relationship

Lookup Tables

Lookup tables provide the means to alter the original pixel values to improve the brightness and contrast of the image.

Image Display

Following computer processing, the digital image is ready to be displayed for viewing. Soft copy viewing refers to the display of the digital image at a computer workstation, as opposed to viewing images on film or another physical medium (hard copy). The quality of the digital image is also affected by important features of the display monitor, such as its luminance, resolution, and viewing conditions such as ambient lighting and monitor placement. Specialized postprocessing software is used at the display workstation to aid the radiologist in image interpretation. In addition to soft copy viewing, the digital image can be printed on specialized film by a laser printer.

Display Monitors

As discussed previously, the quality of the digital image is affected by its acquisition parameters and subsequent computer processing. In addition, the quality of the digital image is affected by the performance of the display monitor. The quality of display monitors may not be equal among all those used for viewing of digital images. Monitors used by radiologists for diagnostic interpretation, referred to as primary, must be of higher quality than the monitors used only for routine image review. However, the radiographer’s monitor should be of sufficiently high quality in order to discern all the image quality characteristics accurately before sending the image to the radiologist for diagnostic interpretation. Display monitors used for diagnostic interpretation are typically monochrome high-resolution monitors and can be formatted as portrait or landscape and configured with one, two, or four monitors (Figure 7-8). A display monitor having diagonal dimensions of 54 cm (21 inches) is adequate to view images sized 35 × 43 cm (14 × 17 inches).

Types of Monitors

Cathode ray tubes (CRTs) and liquid crystal displays (LCDs) are types of monitors typically used for viewing digital images. LCDs are replacing CRTs, and newer technology, such as plasma-type monitors, continue to be developed.

A CRT monitor creates an image by accelerating and focusing electrons to strike the faceplate composed of a fluorescent screen (Figure 7-9). Because the image is scanned on the screen in lines, the number of lines affects the quality of the image displayed. It is recommended that CRT monitors scan at least 525 lines per 130 of a second. The major components of the CRT monitor are the electron gun encasing a cathode, focusing coils and deflecting coils, and the anode. This type of display monitor typically has a curved faceplate, and its dimensions are deeper.