Digital Imaging and Image Manipulation Flashcards

1
Q

first CCD system (3)

A

1988
Radiovisiography
Trophy X-Ray
Vicennes, France
Invented by
Dr. Francis Mouyen

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2
Q

principle of the CMOS detector

A

X-ray → scintillating material → light photos → silicon → electrons
deposited in electron wells and converted to voltage in each pixel→
smoother signal digitization → software processing → images on
monitor

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3
Q

digitization

A

inside the computer, the electronics instantaneously reads the charge in each pixel, converting the charge into 256 or more shades of gray

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4
Q

CMOS
(3)

A

 Newer technology
 Require less power
 Superior image quality

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5
Q

bit depth

A

the number of colors/gray shades that a pixel is able to show

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6
Q

bit depth
number of shades of gray

A

2^(bit)

1 bit (21
) = 2 shades of gray
2 bits (22
) = 4 shades of gray
3 bits (23
) = 8 shades of gray
4 bits (24
) = 16 shades of gray
8 bits (28
) = 256 shades of gray
16 bits (216) = 65,536 shades of gray
24 bits (224) = 16.7 million shades of gray

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7
Q

CCD and PSP plates have been applied in
(2)

A

panoramic and plain skull images

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8
Q

Similar spatial resolution as film-based format :

A

4 lp/mm

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9
Q

Inferior contrast resolution possibly
compensated by

A

manipulation function

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10
Q

why digital imaging is appealing? (4)

A

 Significantly less radiation
 Better image (?)
 Lower costs — more net income
 Environmentally friendly - less toxic chemicals are
disposed into the sewage systems

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11
Q

 Lower costs — more net income (3)

A

 Reduced patient chair time
 No variable costs: film, chemicals
 Elimination of the darkroom

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12
Q

why dental imaging should be appealing? (3)

A

 Electronic communication improves efficiency
 Rapid acquisition
 Image portability

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13
Q

 Image portability
(3)

A
  • storage
  • transmission
  • duplication
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14
Q

general steps in digital image formation (4)

A

X
-ray shadow Shadow image
detected by
digital sensor
Numerical pixel
values sent to the
computer
Digital image
on the computer
screen

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15
Q

 What is image processing?

A

 Mathematical manipulation of image data

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16
Q

 Qualitative
(2)

A

 Uses mathematical operations called matrix
transformations
 Magnify, adjust contrast, brightness, gray scale,
colors, swap black and white

17
Q

Analytical

A

 Measure lengths, pixel values, bone density

18
Q

digital image processing/modifications (4)

A

• Compression
• Imaging manipulations
• Automated image analysis
• Image reconstruction

19
Q

Compression
(4)

A

– affects image file size in memory storage
- useful for storage issues eg. “zipping” files
- actual file size is larger that stored file size
- compression is an algorithm tha can shrink the
file size for storage and recreate the data when
retrieving the data

20
Q

File memory size can become quiet large
due to
(3)

A

– size of grid (sensor size)
- number of images
- bit depth

21
Q

skipped
Imaging manipulations (7)

A

➢ Edge Enhancement – sharpening filter
➢ Noise Reduction – softening filter
➢ Optimization of density/contrast
➢ Inversion of gray scale
➢ Magnification
➢ Emboss function
➢ Pseudocolor enhancement

22
Q

To be able process and construct an image,
the computer will

A

turn the voltage signal to
numbers and then to shades of gray

23
Q

To be able manipulate an image, the computer will
change

A

density values to predetermined numbers
which then changes the image’s presentation i.e.,
lighter darker, etc.
Are post post-display mathematical algorithms that
manipulate the digital signal

24
Q

imaging manipulations
 Depend on
 Make the images subjectively more
 DO NOT increase the

A

viewer preference
appealing
diagnostic
accuracy

25
inversion of gray scale
Reverse the black and white
26
The brightness and contrast adjustments
The brightness and contrast adjustments are done together to subjectively find the “best” combination of brightness and contrast to highlight the clarity of the structures in the image
27
noise reduction may
May degrade or remove important diagnostic information
28
edge enhancement (4)
 Remove low-frequency noise; increases image contrast  Exaggerate the contrast difference between adjacent pixels; to increase contrast, all pixel values are stretched; the dark shades become darker and the light shades become lighter  Enhances local contrast and makes edges sharper to diagnose caries, restoration fit, and fractures  simulates disease; (Is this a good thing?)
29
magnificaiton
Enlarge a specific area till the biggest detail
30
emboss function (inactive)
 Applies a three dimensional effect to the image  Could be useful in presentation situations
31
Automated image analysis (5)
• Length (in MiPACS viewer) • Angles • Bone Density • Area • Circumference • Etc…
32
linear measurement
measurement of the length of the root canal (to within 0.1mm)
33
automated image measurement
Get an exact measurement of the length of the root canal (0.1mm) by using the endo needle as reference
34
Image reconstruction
Data is utilized by other software programs and produces different image presentations