Radiologists are posed with numerous challenges in interpreting direct radiography (DR) and computed radiography (CR) images because of variations in the images’ appearance. This is especially difficult when comparing a DR image from one time with a CR image from another time. The comparison is further complicated by variations in imaging systems from different vendors. The author details a method through which measurements of brightness at various key image points can be used to standardize the visual characteristics of CR and DR radiographs.
is the Radiology Director, Novato Community Hospital, Novato,
Hospitals and imaging centers commonly use a mixture of digital
radiography techniques such as direct radiography (DR), computed
radiography (CR), and mobile DR. Frequently, physicians encounter
challenges when comparing DR and CR images because of inherent
differences in the overall image attributes. These challenges occur
because of different settings in brightness, gray-scale latitude,
harmonized contrast, and edge enhancement.
Adding further variability, physicians may view inpatient images
from a CR system manufactured by one vendor and outpatient images
from a CR system from another manufacturer. This variety in image
appearance has medical implications, since clinicians prefer to
assess patient treatment progress based on an "apples-to-apples"
comparison of images.
In the ideal clinical situation, image appearance differences
resulting from the use of various radiography platforms should be
On occasion, radiologists notice that "the image just doesn't
look right." The cause of inconsistent image quality can originate
from many possible sources, including cassette erasure
difficulties, CR reader problems, processing algorithm issues, and
display monitor deviations.
Since there are many potential sources for image quality
difficulty, a quantitative method to define and establish a
"quality reference image" is needed.
For these reasons, a step-by-step description of a technique to
standardize the appearance of images across platforms would be
useful. The obvious solution to this problem would be to copy and
export postprocessing settings from device A to device B. However,
this solution works only when exporting settings among identically
designed devices (eg, a CR system of one vendor with another CR
system from the same vendor). When cross-platform standardization
is attempted, simply copying software settings does not work
because of the numerous variables (eg, system gray-scale bit depth
and detector sensitivities) that are encountered when moving from
one platform to another.
This article describes a method whereby measurements of
brightness at various key image points can be used to standardize
the visual characteristics of CR and DR radiographs. This technique
is important when attempting to optimize clinical decision-making
when a DR image obtained at time point "A" is compared with a
subsequent CR image at time point "B."
Background:The imaging chain
To understand the key contributing steps to the overall
radiograph appearance, a chain-of-events block diagram is useful.
Figure 1 outlines the steps in the imaging chain from X-ray
exposure to image presentation for both CR and DR techniques. The
goal is to provide a "read-ready" image with consistent at-tributes
(eg, similar gray-scale latitude, edge enhancement, and brightness)
regardless of whether the image followed the DR or the CR chain.
Notably, the steps of X-ray photon capture and detector plate
readout in CR are inherently different from those steps in DR. As a
result, the raw image digital files will look quite different for
these two imaging chains; however, skillful adjustment of the
postprocessing algorithm settings can provide a means to correct
the raw image data.
Tools for comparing digital systems: Phantoms and
To facilitate adjustments to the image-processing algorithms,
the object being radiographed must remain constant.
This is readily accomplished using commercially available
anthropomorphic phantoms (Figure 2). Generally, a full-size chest
phantom and a full-size pelvis phantom can meet the needs of most
centers. Images were obtained using standard radiographic methods
in both the DR and CR rooms of our hospital (Novato Community
Hospital, Novato, CA). Using such phantoms as controls, it is
possible to compare and adjust the image characteristics of various
After initially matching the image settings using subjective
impressions in our department, the standardized look was further
defined using luminance meter measurements obtained directly from
the soft copy view station display (Figure 3). These types of
measurements provide an accurate yardstick for adjusting the
How to standardize your images: A step-by-step
Step 1: The "lead" radiologist chooses a preferred processing
"look" based on a review of several radiographs from the
institution. This is a subjective endeavor, which is easily
accomplished, since there is usually one radiographic system within
the enterprise that produces images that are preferred by most of
the radiologists. Based on this image review, the radiologist
selects a favored "reference" image latitude and brightness.
Step 2: A phantom is radiographed and digitally processed using
the preferred processing parameters. This reference image is then
sent to a picture archiving and communication system (PACS), where
the image can serve as a "gold standard" against which images from
other systems can be compared.
Step 3: The phantom is then radiographed on the other systems at
the hospital, and images are sent for review on a PACS workstation
with medical-grade gray-scale LCD panels. At our institution, the
workstations (MagicView 1000U PACS, Siemens Medical Solutions,
Malvern, PA) are set up with DOME C3 monitors that are calibrated
to the DICOM standard with DOME CXtra calibration software (Planar
Systems, Inc., Waltham, MA).
Step 4: Initial adjustments to the image appearance are made
using subjective assessment of the images during a coordinated
effort between an application specialist who is familiar with the
radiography system and a radiologist who is experienced with
digital image interpretation. The goal is to "tweak" the secondary
system's processing settings so that images roughly match the
agreed-upon favored reference image.
Step 5: Final adjustments to the secondary system are then made
using quantitative luminance measurements (Figure 3) obtained by a
photometer (in our case, an L202 PMS Photometer, Macam Photometrics
Ltd., Livingston, Scotland) that provides readings directly from
the display monitor. These measurements are obtained from 13
locations on the image (Figure 4), and the measurement values can
be graphically displayed on a chart (Figure 5) that shows candelas
per meter squared (cd/m
) versus the sample site.
Step 6: Through coordinated efforts by the application
specialist, the luminance curves of the secondary system are then
brought almost to superimposition with the favored reference system
image by fine-tuning the postprocessing algorithms. Once the final
algorithm is selected, the settings are engaged as the default
algorithms for the imaging system.
The goal: CR/DR images that look similar
Before standardization, the radiographs of the pelvis looked
significantly different, especially regarding the gray-scale
latitude (Figure 6). This subjective finding was confirmed by
photometer measurements (Figure 7). As described above, a favored
reference appearance was selected (in this case, the DR image was
chosen), and adjustments were made so that other images would match
in overall gray-scale and harmonized contrast characteristics
(Figure 8). This matched appearance is possible even though images
came from both CR and DR machines. The photometer measurements can
confirm, on a quantitative basis, a similar image appearance as
documented by improved superimposition and overlap of the
brightness measurement curves (Figure 9). This process was repeated
for several other common examinations, such as lumbar spine, hip,
and chest. Figure 10 shows the improved visual results after
adjustments for the chest radiographs, for which significant
improvement in the luminance curve overlap was accomplished after
normalizing the overall image appearance (Figure 11).
Historically, within a specific platform (eg, a CR system from a
single vendor), images look the same whether the study came from
machine A on the first floor or machine B on the second floor of
the radiology department. However, any large healthcare enterprise
will use several different platforms for obtaining digital
radiographs, and these hardware differences will likely include a
mixture of CR and DR systems. Some installations may even have
multiple vendors providing these radiographic modalities. Because
of differences in image quality and appearance, it is important to
make the image appearance consistent across digital radiography
There are many factors that influence image appearance,
including exposure characteristics (mAs and Kvp), the use of an
antiscatter grid, and properties of the phosphor versus selenium
It is equally important to make preprocessing adjustments to the
histogram during plate readout and adjustments to the
postprocessing algorithms, which are frequently anatomy-specific.
Both pre- and postprocessing influence the final appearance by
dictating the edge enhancement, gray-scale latitude, window-level
settings, and harmonized contrast. Finally, from an observer's
viewpoint, the characteristics of the display monitor also play a
role-ie, there is a noticeable difference between medical-grade
high-brightness, high-contrast gray-scale LCD monitors and
noncalibrated, off-the-shelf, low-brightness color monitors.
Given this complex chain of events (Figure 1), it is not
practical to simply export a collection of settings to provide for
cross-platform uniformity of image quality throughout the
enterprise. While some radiologists and engineers believe that DR
provides better image quality,
as measured by the conspicuity of important findings such as
calcified and noncalcified lung nodules,
others have observed that it is possible to compensate for the
physical differences in detector characteristics with the use of
advanced postprocessing algorithms (such as UNIQUE [UNified Image
Quality Enhancement], Philips Medical Systems, Best, The
Netherlands). This type of processing algorithm provides for
harmonized contrast throughout the image, with particular
enhancement in areas of faint contrast.
The importance of carefully selecting and tuning the
postprocessing algorithms is shown in Figure 12. In this example,
before optimization, the hip radiographs had a wide latitude
appearance. Although that appearance was adequate for diagnosis,
conspicuity of abnormal findings was not optimized. The final
product image, after adjustments of the postprocessing settings,
shows a view that renders anatomic structures with better contrast
and conspicuity of important regions and findings.
With the help of an application specialist, it is possible to
test the appearance of an identical subject in step 1 of the
imaging chain (Figure 1) through the use of a phantom. In turn, the
end point of the imaging chain can be assessed both subjectively
and objectively using the techniques described in this article,
with the goal of normalizing and standardizing image quality across
Although experienced interpreters can mentally compensate for
processing technique differences between images, it requires
additional subjective mental interpolation of images. As a result,
a comparison of 2 different studies from 2 different time points
becomes less accurate and less intuitive. This can be especially
challenging for observers (eg, referring physicians) who do not
practice these types of subjective interpolations. Certainly, it is
possible to partially adjust and normalize the image appearances
using standard window/level adjustments on viewing stations.
However, anatomy-specific postprocessing presets should provide
physicians with images that are "read-ready" and, accordingly,
require only minimal end-user manipulations.