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Digital Radiography – Chapter 11
Adjuncts to Radiology – Chapter 12
Brent K. Stewart, PhD, DABMP
Lois Rutz, M.S. Radiation Safety Engineering, Inc.
a copy of Brent Stewart’s unmodified lecture may be found
at:
http://courses.washington.edu/radxphys/PhysicsCourse04-05.html
Take Away: Five Things You should be able
to Explain after the DR/Adjuncts Lecture
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The various types of detectors used in digital imaging
(e.g., scintillators, photoconductors, etc.)
The differences between the various technologies used
for digital radiography (e.g., CR, indirect and direct DR)
Benefits of each type (e.g., resolution, dose efficiency)
Why digital image correction and processing are
necessary or useful and how they are executed
The various types of adjuncts to radiology (e.g., DSA or
dual-energy imaging), what issue they are trying to
resolve, mechanism exploited and end result
Why Digital/Computed Radiography

Limitations on Film/Screen radiography
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Screen/Film system is image receptor and display
Image characteristics depend on Screen/Film and Film
processing.
Modification of image difficult to control (e.g. development
temperature).
Image appearance depends on technique settings.
Image quality cannot be repaired after development. Retake
only solution to poor I.Q.
Why Digital/Computed Radiography cont.

Screen/film dynamic range 2 to 2.5 orders of magnitude.

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Different applications require different screen/film combinations.
Only one “original” image.
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Films often “go missing” from ER or ICU and never are archived.
Copies expensive, have inconsistent quality, and often are nondiagnostic.
Archive space expensive, often remote.
Digitizing film is only way to move images to PACS.
How does Digital/Computed Radiography solve
these problems?
• Decouples imaging chain components.
• Detector, image processing, display all “independent” entities.
• Independent in design but not in application.
• Detector can make use of extended dynamic range.
• Solid state detectors have improved DQE.
• Electronics can apply corrections to input signals.
• In particular, over/under exposure can be corrected, reducing
retakes.
How does Digital/Computed Radiography solve
these problems? Cont.
• Image processing can modify and enhance raw (preprocessed) data.
• Images can be displayed on workstations which permit
interactive display processing.
• Image data is stored digitally. “Original image” is
available everywhere and at any time.
CR vs. DR

CR also known as a Photostimulable Phosphor system.


CR uses an imaging plate similar to an intensifying screen as the
receptor.
CR systems are indirect digital systems.


Indirect systems convert x-radiation to the final digital image through
one or more stages.
DR digital radiography


Uses a fixed detector such as amorphous selenium plate as the
receptor.
Can be a direct or an indirect digital system.

When direct it is sometimes called DDR for direct digital radiography
CR

Detector or Imaging Plate (IP) is essentially a type of
intensifying screen.
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IP can be used in any bucky or table-top system.
IP is relatively robust. Requires same care as intensifying
screens.
Process is indirect.
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X-ray creates excitation center.
Plate reader uses red light to stimulate centers to release blue
light.
Blue light is directed to a photo-electric transducer (pmt or other).
Electric signal digitized to make raw image.
CR and DR Systems
Image Production in CR/DR Systems
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Radiation through the patient creates a latent image on the receptor.
Receptor is “read” by some process and latent image is converted to
an electronic signal.
Signal is processed.
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Signal (analog) is converted via ADC to a bit value in a digital matrix.
Digital image is processed.
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Processing is related to acquisition system characteristics.
Processing is related to desired image information.
Digital matrix is displayed on a video screen or printed to paper or
film.
Signal Processing
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Primarily to accommodate variations in the
detector/electronics components.
Involves corrections for dead space, non-uniformities,
defects.
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Could be developed to compensate for MTF losses.
All systems, PSP or Direct, do some sort of processing
and scaling.
Ultimate goal is to present the image processing module
with “true” image pixels.
Digital Image Correction
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Interpolation to fill in dead pixel and row/column defects
Subtracting out average dark noise image Davg(t)(x,y)
Differences in detector element digital values for flat field
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Make corrections for each detector element (map)
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Gain image: G(x,y) =G’(x,y) - Davg(t)(x,y); Gavg =(1/N) ∙   G(x,y)
I(x,y) = Gavg ∙ [Iraw(x,y) - Davg(t)(x,y)] / G(x,y)
Done for DR and in a similar manner for CT (later)
Not performed for CR on a pixel by pixel basis, although
there are corrections on a column basis for differences in
light conduction efficiency in the light guide to the PMT
Digital Image Correction
c.f. Bushberg, et al. The Essential Physics of Medical Imaging, 2 nd ed., p. 310.
Detectors

In order to understand signal processing we need to
learn about the detectors.
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Photo Stimulable Phosphor Plates
Photoconductive materials.
Detector consists of a receptor material (e.g. BaF(H)Eu),
and a set of signal readout and conversion electronics.
Receptor responsible for the DQE.

Rest of the system contributes to noise, resolution,dynamic
range.
Detectors in Digital Imaging (1)
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Gas and solid-state detectors
Energy deposited to e- through
Compton and photoelectric
interactions
Gas detectors – apply high
voltage across a chamber and
measuring the flow of eproduced by ionization in the
gas (typically high Z gases like
Xenon: Z=54, K-edge = 35
keV)
Were used in older CT units
c.f. Bushberg, et al. The Essential Physics of
Medical Imaging, 2nd ed., p.32.
Detectors in Digital Imaging (2)

Solid-state materials
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Electrons arranged in bands with conduction band usually empty
Solid-state detectors
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Scintillators – some deposited energy converted to visible light
Photoconductors – charge collected and measured directly
Photostimulable phosphors – energy stored in electron traps
c.f. Yaffe MJ and Rowlands JA. Phys. Med. Biol. 42 (1997), p. Elements of Digital Radiology, p. 10.
Detectors in Digital Imaging (3)
c.f. Yaffe MJ and Rowlands JA. Phys. Med. Biol. 42 (1997), p. Elements of Digital Radiology, p. 9.
Computed Radiography (CR)
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Photostimulable phosphor (PSP)
Barium fluorohalide: 85%
BaFBr:Eu + 15% BaFI:Eu
e- from Eu2+ liberated through
absorption of x-rays by PSP
Liberated e- fall from the
conduction band into ‘trapping
sites’ near F-centers
By low energy laser light (700 nm)
stimulation the e- are re-promoted
into the conduction band where
some recombine with the Eu3+
ions and emit a blue-green (400500 nm) visible light (VL)
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 295.
Computed Radiography (CR) System (1)
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Imaging plate (IP) made of PSP is
exposed identically to SF
radiography in Bucky
IP in CR cassette taken to CR
reader where the IP is separated
from cassette
IP is transferred across a stage
with stepping motors and scanned
by a laser beam (~700 nm) swept
across the IP by a rotating
polygonal mirror
Light emitted from the IP is
collected by a fiber-optic bundle
and funneled into a photomultiplier
tube (PMT)
PMT converts VL into e- current
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 294.
Computed Radiography (CR) System (2)
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Electronic signal output from PMT
input to an ADC
Digital output from ADC stored
Raster swept out by rotating
polygonal mirror and stage
stepping motors produces I(t) into
PMT which eventually translates
into the stored DV(x,y):
PMT→ADC→RAM
IP exposed to bright light to erase
any remaining trapped e- (~50%)
IP mechanically reinserted into
cassette ready for use
200mm and 100mm pixel size (14”x17”: 1780x2160 and
3560x4320, respectively)
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 294.
Indirect Flat Panel Detectors
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Use an intensifying screen
(CsI) to generate VL photons
from an x-ray exposure
Light photons absorbed by
individual array photodetectors
Each element of the array
(pixel) consists of transistor
(readout) electronics and a
photodetector area
The manufacture of these
arrays is similar to that used in
laptop screens: thin-film
transistors (TFT)
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 301.
Charged-Coupled Devices (CCD)
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Form images from visible light
Videocams & digital cameras
Each picture element (pixel) a
photosensitive ‘bucket’
After exposure, the elements
electronically readout via ‘shiftand-read’ logic and digitized
Light focused using lenses or
fiber-optics
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Fluoroscopy (II)
Digital cineradiography (II)
Digital biopsy system
(phosphor screen)
1K and 2K CCDs used
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., pp. 298-299.
Direct Flat Panel Detectors
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Use a layer of photoconductive
material (e.g., α-Se) atop a TFT
array
e- released in the detector layer
from x-ray interactions used to
form the image directly
X-ray→e-→TFT → ADC→RAM
High degree of e- directionality
through application of E field
Photoconductive material can be
made thick w/o degradation of
spatial resolution
Photoconductive materials
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Selenium (Z=34)
CdTe, HgI2 and PbI2
Indirect Flat Panel Detector (for comparison)
Direct Flat Panel Detector
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 304.
Thin-Film Transistors (TFT)
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After the exposure is complete
and the e- have been stored in
the photodetection area
(capacitor), rows in the TFT
are scanned, activating the
transistor gates
Transistor source (connected
to photodetector capacitors is
shunted through the drain to
associated charge amplifiers
Amplified signal from each
pixel then digitized and stored
X-ray→VL→e-→ADC→RAM
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 301.
Resolution and Fill Factor
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Dimension of detector element largely determines spatial resolution
200mm and 100mm pixel size typical
For dimension of ‘a’ mm - Nyquist frequency: FN = 1/2a
If a = 100mm → FN = 5 cycle/mm
Fill factor = (light sensitive area)/(detector element area)
Trade-off between spatial resolution and contrast resolution
c.f. Bushberg, et al. The Essential Physics of Medical Imaging, 2 nd ed., p. 303.
Image Digitization and Processing

After acquisition and correction of raw data, the image is
ready for display processing.

The image data consists of a matrix of numbers. Each
pixel is one matrix point. Each gray scale is a digital
value.

For example: a matrix can have 1024 x 1024 pixels and each
pixel will have a value from 0 to 1024. Each value is related to
the radiation exposure which created that pixel.
Digital Storage of Images
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Usually stored as a 2D array
(matrix) of data, I(x,y): I(1,1),
I(2,1), … I(n,m-1), I(n,m)
Each minute region of the
image is called a pixel (picture
element) represented by one
value (e.g., digital value, gray
level or Hounsfield unit)
Typical matrices:
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CT: 512x512x12 bits/pixel
CR: 1760x2140x10 bits/pixel
DR: 2048x2560x16 bits/pixel
c.f. Huang, HK. Elements of Digital Radiology, p. 8.
Image Processing
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Image data is scaled to present image with appropriate
gray scale (O.D.) values regardless of the actual
radiation used to produce the image.
Image data is frequency enhanced around structures of
importance.
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Process involves mathematical filters.
Image data is display processed to give desired contrast
and density.
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Process involves re-mapping along a chosen display (“H&D”)
curve
Generic Display Processing

Different manufacturers may use different versions of
generic image processing methods.
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E.g. Musica, Ptone
All describe means of scaling and modifying image appearance.
Different manufacturers use different exposure
indicators.
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E.g. EI, S, IgM
All describe the relationship between the exposure to the
detector and the pixel value.
Generic Elements of Display Processing
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Exposure Recognition.
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Signal Equalization:
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Adjust regions of low/high signal value
Grayscale Rendition
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Adjust for high/low average exposure
Convert signal values to display values
Edge Enhancement:
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Sharpen edges

M. Flynn, RSNA 1999
Image Processing
normalized histogram comparison
fraction of pixels in ROI
0.025
0.02
0.015
ph1.2
ptx case 4
0.01
0.005
0
0
0.2
0.4
0.6
normalized pixel value
0.8
1
Computed Radiography (CR) System (3)
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IP dynamic range = 104, about
100x that of S-F (102)
Very wide latitude → flat contrast
Image processing required:
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Enhance contrast
Spatial-frequency filtering
CR’s wide latitude and image
processing capabilities produce
reasonable OD or DV for either
under or overexposed exams
Helps in portable radiography:
where the tight exposure limits of
S-F are hard to achieve
Underexposed → ↑ quantum
mottle and overexposed →
unnecessary patient dose
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 296.
Unsharpmasked Spatial Frequency Processing
c.f. Bushberg, et al. The Essential Physics of Medical Imaging, 2 nd ed., p. 313.
Global Processing
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Most common global image
processing: window/level
Global processing algorithm
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I’(x,y) = c ∙ [I(x,y) – a]:
essentially y = mx + b
Level (brightness) set by a
Window (contrast) set by c
I’ = [2N/ww]∙[I-{wl-(ww/2)}],
where ww = window width and
wl = window level
Need threshold limits when
max/min [2N-1, 0] digital
values encountered
If I’(x,y) > Tmax→I’(x,y) = Tmax
If I’(x,y) < Tmin→I’(x,y) = Tmin
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., pp. 92 and 311.
Image Processing Based on Convolution
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Convolution: Ch. 10 - Image
Quality and Ch. 13 - CT
Defined mathematically as
passing a N-dimensional
convolution kernel over an Ndimensional numeric array (e.g.,
2D image or CT transmission
profile)
At each location (x, y, z, t, ...) in
the number array multiply the
convolution kernel values by the
associated values in the numeric
array and sum
Place the sum into a new numeric
array at the same location
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 312.
Image Processing Based on Convolution
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Delta function kernel
0
0
0
0
1
0
0
0
0
Blurring kernel (normalization)
also known as low-pass filter
1/9
1/9
1/9
1/9
1/9
1/9
1/9
1/9
1/9
Edge sharpening kernel
-1
-1
-1
-1
9
-1
-1
-1
-1
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 313.
Image Processing Based on Convolution
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Convolution kernels can be much larger than 3 x 3, but
usually N x M with N and M odd
Can also perform edge sharpening by subtracting
blurred image from original → high-frequency detail
(harmonization)
The edge sharpened image can then be added back to
the original image to make up for some blurring in the
original image: CR unsharpmasking - freq. processing
The effects of convolution cannot in general be undone
by a ‘de-convolution’ process due to the presence of
noise, but a deconvolution kernel can be applied to
produce an approximation: 19F MRI
Median and Sigma Filtering
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Convolution of an image with a kernel where all the
values are the same, e.g. (1/NxM), essentially performs
an average over the kernel footprint
Smoothing or noise reduction
This can make the resulting output value susceptible to
outliers (high or low)
Median filter: rank order values in kernel footprint and
take the median (middle) value
Sigma filter: set sigma (s) value (e.g., 1) and throw out
all values in kernel footprint > m + s or < m – s and then
take the average and place in output image
Multiresolution/Multiscale Processing and
Adaptive Histogram Equalization (AHE)
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Some CR systems (Agfa/Fuji) make use of
multiresolution image processing (AKA unsharpmasking)
to enhance spatial resolution
Wavelet or pyramidal processing on multiple frequency
scales
Histogram equalization re-distributes image digital
values to uniformly span the entire digital value range
[2N-1,0] to maximize contrast
AHE does this on a spatial sub-region basis in an image
rather than the entire image
Fuji ‘Dynamic Range Control’ (DRC) a version of AHE
that operates on sub-regions of digital values
Histogram Equalization
Properly Exposed Image
Under-exposed Image
Over-exposed Image
Histogram Equalized Image
c.f. http://www.wavemetrics.com/products/igorpro/imageprocessing/imagetransforms/histmodification.htm
Global and Adaptive Histogram Equalization
The following images illustrate
the differences between global
and adaptive histogram
equalization.
MR image with the corresponding gray-scale
histogram. The histogram has a peak at
minimum intensity consistent with the
relatively dark nature of the image.
Global histogram equalization and the final
gray-scale histogram. Comparing the results
with the figure above we can see that the
distribution was shifted towards higher values
while the peak at minimum intensity remains.
Adaptive histogram equalization shows better
contrast over different parts of the image. The
corresponding gray-scale histogram lacks the
mid-levels present in the global histogram
equalization as a result of setting a high contrast
level.
c.f. http://www.wavemetrics.com/products/igorpro/imageprocessing/imagetransforms/histmodification.htm
Contrast vs. Spatial Resolution in Digital Imaging
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S-F mammography can
produce images w/ > 20 lp/mm
According to Nyquist criterion
would require 25 mm/pixel
resulting in a 7,200 x 9,600
image (132 Mbytes/image)
Digital systems have inferior
spatial resolution
However, due to wide dynamic
range of digital detectors and
image processing capabilities,
digital systems have superior
contrast resolution
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 315.
Digital Imaging Systems and DQE
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Remember the equation for
2
DQE(f)?
k MTF (f )
DQE(f) =


N  NPS(f )
How can we account for this?
Both CR and the screens in
film/screens made thin
Film higher spatial resolution
than CR
DQE higher for α-Si systems
using CsI and Gd2O2S rather
than α-Se (mean x-ray E & Z)
α-Si DQE falling off more
rapidly than α-Se (geometry)
α-Si DR
α-Se DR
Digital versus Analog Processes & Implementation

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
Although some of the previous image reception systems
were labeled ‘digital’, the initial stage of those devices
produce an analog signal that is later digitized
CR: x-rays→VL→PMT→current→voltage→ADC
CCD, direct & indirect digital detectors: stored e- → ADC
Benefits of CR

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Same exam process and equipment as screen-film radiography
Many exam rooms serviced by one reader
Lower initial cost
Benefits of DR

Throughput ↑: radiographs available immediately for QC & read
Patient Dose Considerations

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Over and underexposed digital receptors produce
images with reasonable OD or gray scale values
As overexposure can occur, need monitoring program
CR IP acts like a 200 speed S-F system wrt. QDE
Use the CR sensitivity (‘S’) number to track dose
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Bone, spine and extremities: 200
Chest: 300
General imaging including abdomen and pelvis: 300/400
Flat panel detectors can reduce radiation dose by 2-3x
as compared with CR for the same image quality due to
↑ quantum absorption efficiency & conversion efficiency
Using the CR Sensitivity Number to Track Dose
S-number Dashboard
Main Exams
500
450
Sep-03 Baseline
Mar-04
Apr-04
400
S-number
350
300
Target Values
250
Fixed Chest - [255-345]
200
Bone, Spine & Ext [170-230]
150
100
General Imaging incl.
Abdomen - [340-460]
50
0
MFEM
MC2
MC5
MCH2
Exam Code
MKUB
MPELV
Huda Ch6: Digital X-ray Imaging Question

12. Photostimulable phosphor systems do NOT include:

A. Analog-to-digital converters
B. Barium fluorohalide
C. Light detectors (blue)
D. Red light lasers
E. Video cameras

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

Huda Ch6: Digital X-ray Imaging Question

11. Which of the following x-ray detector materials emits
visible light:

A. Xenon
B. Mercuric iodide
C. Lead iodide
D. Selenium
E. Cesium iodide




Raphex 2002 Question: Digital Radiography

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
D47. Concerning computed radiography (CR), which of
the following is true?
A. Numerous, small solid-state detectors are used to
capture the x-ray exposure patterns.
B. It has better spatial resolution than film.
C. It is ideal for portable x-ray examinations, when
phototiming cannot be used.
D. It is associated with high reject/repeat rates.
E. The image capture, storage, and display are
performed by the receiver.
Huda Ch6: Digital X-ray Imaging Question

13. Photoconductors convert x-ray energy directly into:

A. Light
B. Current
C. Heat
D. Charge
E. RF energy




Huda Ch6: Digital X-ray Imaging Question

15. Which of the following does NOT involve image
processing:

A. Background subtraction
B. Energy subtraction
C. Histogram equalization
D. K-edge filtering
E. Low-pass filtering




Huda Ch6: Digital X-ray Imaging Question

14. Processing a digital x-ray image by unsharpmask
enhancement would increase the:

A. Bit depth per pixel
B. Matrix size
C. Patient dose
D. Visibility of edges
E. Limiting spatial resolution

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
Adjuncts and other interesting stuff
Geometric (Linear) Tomography

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
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 318.
With the advent of CT, geometric
tomography has only limited
clinical utility where only one or a
few planes of objects with high
contrast are desired, e.g., IVP
Desired slice through patient set
at pivot point (focal plane)
The tomographic process blurs
out regions outside the focal
plane, but still contributes to
overall loss of contrast
Larger tomographic angles result
in a lessening of out of plane
contributions
High dose, comparable to CT for
many tomographic slices
Digital Tomosynthesis




Improved version of geometric
tomography where a digital
detector saves an image at
each of several tube angles
This allows reconstruction of
multiple planes through the
object through shifting the
various images through a
certain distance before
summing them
Much more dose efficient, but
still suffers from out of plane
blurring effects
Either CR or DR used
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 320.
Temporal Subtraction




Digital Subtraction Angiography
(DSA) – usually 1K resolution
Mask (background) subtracted
from images during/post contrast
injection: Δ < 1% trans. visualized
Motion can cause misregistration
artifacts
Digital value proportional to
contrast concentration and vessel
thickness



Is = ln(Im) – ln(Ic) = mvessel ∙ tvessel
Temporal subtraction works best
when time differences between
images is short
Possible to spatially warp images
taken over a longer period of time
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 322.
Dual-Energy Subtraction





Exploits differences between
the Z of bone (Zeff ≈ 13) and
soft tissue (Zeff ≈ 7.6)
Images taken either at two
different kVp (two-shot)
One image (one-shot) taken
with energy separation
provided by a filter (sandwich)
Iout = loge(Ilow) – R ∙ loge(Ihigh),
where R is altered to produce
soft-tissue predominant or
bone predominant images
GE Chest DR @ SCCA
c.f. Bushberg, et al. The Essential Physics of Medical
Imaging, 2nd ed., p. 324.
Dual-Energy Subtraction
c.f. Bushberg, et al. The Essential Physics of Medical Imaging, 2 nd ed., p. 325.
Huda Ch6: Digital X-ray Imaging Question

22. The matrix size in a DSA image is typically:

A. 128 x 128
B. 256 x 256
C. 512 x 512
D. 1024 x 1024
E. 2048 x 2048




Huda Ch6: Digital X-ray Imaging Question

25. Changing the DSA matrix from 10242 to 20482 would
NOT increase the:

A. Data digitization rate
B. Data storage requirement
C. Image processing time
D. Spatial resolution
E. Pixel size




Raphex 2003 Question: Digital Radiography






D51. A flat panel digital radiographic detector has a
square 20 x 20 cm image receptor field. The full field of
the detector is coupled to a nominal 2048 x 2048 CCD
array. The relative spatial resolution (lp/mm) when going
from a 20 x 20 cm to a 10 x 10 cm field of view is:
A. Four times better
B. Twice as good
C. The same
D. Half as good
E. One fourth as good
Huda Ch6: Digital X-ray Imaging Question

17. The Nyquist frequency for a 1K digital photospot
image (25 cm image intensifier diameter) is:


A. 1 lp/mm
B. 2 lp/mm
C. 4 lp/mm
D. 8 lp/mm
E. 10 lp/mm

FN (lp/mm) = 1/2a = 1/2(1024 lines/250 mm) = 2.048 ≈ 2



Digital Representation of Data (1)

Bits, Bytes and Words




Smallest unit of storage capacity = 1 bit (binary digit: 1 or 0)
Bits grouped into bytes: 8 bits = byte
Word = 16, 32 or 64 bits, depending on the computer system
addressing architecture
Computer storage capacity is measured in:




kilobytes (kB) - 210 bytes = 1024 bytes  a thousand bytes
megabytes (MB) - 220 bytes = 1024 kilobytes  a million bytes
gigabytes (GB) - 230 bytes = 1024 megabytes  a billion bytes
terabytes (TB) - 240 bytes = 1024 gigabytes  a trillion bytes
Digital Representation of Data (2)

Digital Representation of Different Types of Data


Alphanumeric text, integers, and non-integer data
Storage of Positive Integers






In general, n bits have 2n possible permutations and can
represent integers from 0 to 2n-1 (the range usually denoted with
square brackets):
n bits represents 2n values with range [0, 2n-1]
8 bits represents 28 = 256 values with range [0, 255]
10 bits represents 210 = 1024 values with range [0, 1023]
12 bits represents 212 = 4096 values with range [0, 4095]
16 bits represents 216 = 65,536 values with range [0, 65535]
Conversion of Analog Data to Digital Form



The electronic measuring devices of medical scanners (e.g.,
transducers and detectors) produce analog signals
Analog to digital conversion (analog to digital converter – ADC)
ADCs characterized by


sampling rate or frequency (e.g., samples/sec – 1 MHz)
number of bits output per sample (e.g., 12 bits/sample = 12-bit ADC)
c. f. Bushberg, et al., The Essential Physics of Medical Imaging, 2nd ed., p. 69.
Periodic Table of the Elements
c.f. http://www.ktf-split.hr/periodni/en/