5. Digital Radiographic Image Processing and Manipulation Flashcards
The images are processed to mimic the appearance of
screen-film images
DIGITAL PROCESSING WILL ALSO
ADJUST FOR TECHNICAL ERRORS:
• allow for a wider range of subject contrast
• enhance the spatial frequency of certain tissues
or regions of interest
• allow the radiologist to highlight certain areas of
interest, often with special processing functions
2 STEPS IN IMAGE PROCESSING
- Preprocessing
2. Postprocessing
Occurs prior to the image being displayed
Preprocessing
algorithms determine the image histogram
Preprocessing
detector defects are removed
Preprocessing
noise corrections are performed
Preprocessing
Done by technologist to prepare the image for the
radiologist through various user functions
Postprocessing
May also be performed by radiologist to produce
specialized images to aid the radiologist in a
diagnosis
Postprocessing
is a graph of the number of pixels in the entire
image or part of the image having the same gray levels (density
values), plotted as a function of the gray levels
Image Histogram
y-axis
Number of Pixels or Frequency of occurrence of various gray levels
x-axis
Pixel Intensity
gray value
representing the
strength of the
acquired signal
Horizontal Axis
Pixel intensity
Horizontal Axis
Number of pixels in
each tone
Vertical Axis
____ of the graph represent black areas (greater acquired signal)
One End
Example: Air
shade of gray, representing medium tones
Middle Area
Example: Soft tissue, muscle
represents white (no acquired signal)
Extreme Opposite Area
Example: Bone
This graphic representation appears as a pattern of peaks and valleys
that varies for each body part
Image Histogram
creates a wider histogram
Low energy (low kVp)
long scale of contrast
Low energy (low kVp)
creates a narrow histogram
High energy (high kVp)
short scale of contrast
High energy (high kVp)
Analysis of the histogram is very
complex
The shape of the histogram is ____ specific
anatomy
It is important to choose the correct _____ on the
menu for the body part exposed
anatomic region
Digital Radiography Signal Sampling
- The Nyquist Theorem
- Aliasing
- Rescaling
- Look-up Table
described a way to convert analog signals into digital
signal that would more accurately transmit over telephone lines
1928 – Harry Nyquist
Sampling
Nyquist Theorem
states that when sampling a signal (ADC)
the sampling frequency must be greater than twice the frequency of the input signal so that the reconstruction of the
original image will be as close to the original signal as possible
Nyquist Theorem
In digital imaging, at least \_\_\_\_ the number of pixels needed to form the image must be sampled
twice
If too few pixels are sampled, the result will be a
lack of resolution
when the spatial frequency is greater than the Nyquist frequency & the sampling occurs less than twice per cycle, information is lost and a
fluctuating signal is produced
Aliasing
Undersampling
Aliasing
when the (fluctuating) signal is reproduced, frequencies above the Nyquist frequency causes
Aliasing (Foldover or Biasing)
causes mirroring
of the signal at ¼ the frequency
Aliasing (Foldover or Biasing)
a wraparound image is produced, which
appears as two superimposed images
that are slightly out of alignment, resulting in a
Moire effect
when exposure is greater or less than what is needed to produce an image, it occurs in an effort to display the pixels for the area of interest
Automatic Rescaling
means that images are produced with uniform brightness and contrast,
regardless of the amount of exposure used to acquire the image
Automatic Rescaling
Histogram of the luminance values derived during image
acquisition
Look-up Table
Used as a reference to evaluate the raw information & correct the
luminance values
Look-up Table
This is a mapping function in which all pixels (each with its own
specific gray value) are changed to a new gray value
Look-up Table
are data stored in the computer that is used to
substitute new values for each pixel during the processing
Look-up Table (LUT)
The resultant image will have the appropriate appearance in
brightness and contrast
Look-up Table (LUT)
There is a ___ for every
anatomic part
LUT
The LUT can be graphed by plotting the original values ranging from ____ on the horizontal axis and the new values (0-255) on the vertical axis
0 to 225
displayed as black
< 50
displayed as white
> 250
displayed as shades of
gray
50-150
Quality Control
Workstation Functions
Image Processing Parameters
- Contrast Manipulation
- Spatial Frequency Resolution
- Spatial Frequency Filtering
Spatial Frequency Filtering
- Edge Enhancement
2. Smoothing
Converting the digital input data to an image with appropriate
brightness and contrast using contrast enhancement
parameters
Contrast Manipulation
No amount of adjustment can take the place of ____ technical
factors selection
proper
Ability of an imaging system to differentiate between two near-by objects
Spatial Frequency Resolution
The detail or sharpness of
an image
Spatial Frequency Resolution
A large pixel size will be
unable to resolve two near-by structures as compared
to a small pixel size
Spatial Frequency Resolution
Measured in lp/mm
Spatial Frequency Resolution
high-pass filtering
Edge Enhancement
Occurs when fewer pixels in the neighborhood are included in the signal average
Edge Enhancement
useful for enhancing large structures such as organs and soft tissue, but it can be noisy
Edge Enhancement
low-pass filtering
Smoothing
Occurs by averaging each pixel’s frequency with surrounding
pixel values to remove high-frequency noise
Smoothing
Useful for viewing small structures such as fine bone tissues
Smoothing
Basic Functions of the
Processing System
Post-Processing Image Manipulation
- Window Level & Window Width
- Background Removal or Shuttering
- Image Stitching
- Image Annotation
- Magnification
Most common image post-processing parameters are those for _____ and _____
brightness, contrast (Window Width & Level)
controls how bright or dark the screen image is.
Window Level
controls the ratio of the black and white, or contrast
Window Width
The higher the level is, the ____ the image will be, and the wider the
window width, the ____ the contrast
darker (higher),
lower (wider)
excess light
Veil Glare
is used to blacken out the white collimation borders,
effectively eliminating veil glare
Automatic shuttering
unexposed borders around
the collimation edges
allows excess light to enter
the eye
Veil Glare
causes oversensitization of
a chemical within the eye
called _____
Veil Glare,
rhodopsin
results in temporary white
light blindness
Veil Glare
Removing the white unexposed borders results in an overall smaller number of pixels & ____ the amount
of information to be stored
reduces
refers to the way anatomy
is oriented on the imaging
plate
Image Orientation
The image is displayed
exactly as it was read
unless the reader is
informed differently
Image Orientation
When anatomy or the area of interest is too large to fit on one
cassette, multiple images can be “_____” together using specialized
software programs
stitched (Image Stitching)
allows selection of preset terms and/or manual text input & can
be particularly useful when such additional information is necessary
Image Annotation
a box placed over a small segment of anatomy on the main image
shows a magnified version of the underlying anatomy
Magnification
Magnification of the entire image
pan navigation
Image Management
- Patient Demographic Input
- Manual Send
- Archive Query
Proper identification of the patient is even more critical with digital images than with conventional hard copy film/screen
images
Patient Demographic Input
Patient Demographic Input Includes:
- patient name
- health-care facility
- patient identification number
- date of birth
- examination date
arise if the patient name is entered differently from visit to visit or examination to examination
Problems
This function allows the QC technologist to select one or more local computers to receive images
Manual Send
Most QC workstations are set to automatically send a completed
image to the appropriate destinations
Manual Send
function that allows retrieval of images from the PACS based on
date of examination, patient name or number, examination number,
pathologic condition or anatomic area
Archive Query
