ct seeram chapter #3: digital imaging. analog vs. digital information analog continuous information...
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CT
Seeram Chapter #3:Digital Imaging
Analog vs. Digital Information
Analogcontinuous informationCan have any of an infinite
number of values
Digitaldiscrete informationCan have a finite number of
values limited by # of digits on display # of bits used to represent
value
Analog vs. Digital ImagesAnalog
continuous spatial information
Digital• discrete spatial
information
Digitizing a PictureCommercial scannerRenders a photograph into numbers
311, 255, 309, 78, 43, 99, 124,…
Analog vs. Digital ImagesAnalog
continuous gray shade information
DigitalDiscrete gray
shade information
Digital Image FormationDigital Image FormationClinical ImageScreen Wire Mesh
Digital Image Formation:SamplingDigital Image Formation:Sampling
Place mesh over image
Assign each square (pixelpixel) a value based on density
Pixel values form the digital image
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Digital Image Formation:SamplingDigital Image Formation:Sampling
Each pixel assigned a value
Value averages entire pixelAny spatial
variation within a pixel is lost
The larger the pixel, the more variation
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Digital Image FormationDigital Image Formation The finer the mesh (sampling), the more accurate the digital
rendering
What is this?What is this?
12 X 9 Matrix
Same object, smaller squaresSame object, smaller squares
24 X 18 Matrix
Same object, smaller squaresSame object, smaller squares
48 X 36 Matrix
Same object, smaller squaresSame object, smaller squares
96 X 72 Matrix
Same object, smaller squaresSame object, smaller squares
192 X 144 Matrix
The BitThe Bit
Fundamental unit of Fundamental unit of computer storagecomputer storage
Only 2 allowable valuesOnly 2 allowable values01
Computers do all operations with 0’s & 1’s
BUT
Computers group bits together
Popular Bit GroupingsPopular Bit GroupingsBitBit (binary digit)
Smallest binary unit; has value 0 or 1 onlyByteByte
8 bits28 = 256 unique values
WordWord16 bits216 = 65536 unique values
Double WordDouble Word32 binary bits
(1110 0100 0000 1011 0101 0101 1110 0101)
# of values which can be # of values which can be represented by 1 bitrepresented by 1 bit# of values which can be # of values which can be represented by 1 bitrepresented by 1 bit
2 unique combinations / values
1
2
# of values which can be # of values which can be represented by 2 bitsrepresented by 2 bits# of values which can be # of values which can be represented by 2 bitsrepresented by 2 bits
4 unique combinations / values2
1
3
4
# of values which can be # of values which can be represented by 3 bitsrepresented by 3 bits# of values which can be # of values which can be represented by 3 bitsrepresented by 3 bits
8 unique combinations / values
2
1
3
4
6
5
7
8
Digital Image Bit DepthDigital Image Bit Depthbit depth controls # of possible values a pixel can
haveincreasing bit depth results in
more possible values for a pixelbetter contrast resolution
1 2 3 ...8
0, 100, 01, 10, 11000, 001, 010, 011, 100, 101, 110, 111...00000000, 00000001, ... 11111111
2 1 = 22 2 = 42 3 = 8...2 8 = 256
Bits Values # Values
# of Possible Values & Contrast Resolution# of Possible Values & Contrast ResolutionThe more possible values for a pixel, the more
gray shades & the better the contrast.
4 grade shades 256 grade shades
Digital Image FormationQuantization (A to D Conversion)Digital Image FormationQuantization (A to D Conversion)Process of
assigning a number to a gray shade
Only discrete #’s assignedcan lose
information because of discrete # assignment
88 ? 89
The middle pixel attenuates between the other two. What # will the A to D converter assign it?
Analog to Digital ConverterAnalog to Digital Converter
88 ? 89
Since there are no #’s between 88 & 89 (88.5 not allowed), the A to D converter will assign pixel either a 88 or a 89.
The fact that the center pixel is darker than the left one and lighter than the right one is forever lost.
Contrast ResolutionContrast Resolution
difference in x-ray attenuation required for 2 pixels to be assigned different digital values
89
88
Gray ScaleGray Scale
the more candidate values for a pixelthe more shades of gray image
can be stored in digital imageThe less difference between x-ray
attenuation required to guarantee different pixel values See next slide
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1 2 6 6 4 4 5 3 2 3 7 7 6 4 2 5 5 2
1234567
2 4 11 11 7 8 10 6 3 6 14 14 11 6 4 8 12 4
89
1011121314
Setting pixel values
Display LimitationsDisplay Limitationsnot possible to display all shades of gray
simultaneouslywindow & level controls determine how pixel
values are mapped to gray shades numbers (pixel values) do not change;
window & level only change gray shade mapping
17 =
65 =
Change window / level
17 =
65 =
Presentation of Brightness LevelsPresentation of Brightness LevelsPre-processing
Assignment of values to a pixelIn CT values assigned according to attenuation
Post-processingEach pixel value assigned a brightnessDynamic process
Assigned brightness for a particular pixel values can be changeg Window Level
Does not affect image data
125 25 311 111 182 222 176
199 192 85 69 133 149 112
77 103 118 139 154 125 120
145 301 256 223 287 256 225
178 322 325 299 353 333 300
Digital Image Sources
CTMRICRDRDigital Subtraction AngiographyUltrasoundNuclear Medicine
Why Digital?Required for
computer usePerfect image copiesCompression
Reduction of image size in computer
Why Digital?o Image Manipulation
o Rotationo White/black reversalo Zoomo Window/level
o Enhancemento Edge enhancemento Smoothing (noise reduction)
o Analysiso Image statisticso Pattern recognition
Image Processing Techniques
Point OperationsSpatial Frequency
FilteringGeometric Operations
Some Operation
Input Pixel Values
Don’t Change
Output / Display Pixel Values(Gray shades)
Altered by Operation
Point OperationsValue of each pixel altered according to some
ruleNew pixel values assigned on pixel by pixel basis
independent of adjoining pixels
Example: Gray level mapping: window / levelLook-up table (LUT) altered
Maps pixel value to gray shades
HistogramGraph showing # of pixels at each gray
shadeAltered by point operations
1 2 3 4 5 6 7 8 9 10 11
Pixel Value
#
1 2 3 4 5 6 7 8 9 10 11
Pixel Value
#
Local Operations
AKAArea processesGroup processes
Modification of input pixel based upon values of pixels close by
Local Operations
High frequency imagebrightness changes rapidly with distanceSmall pixels required
Low frequency imagebrightness changes slowly with distance
Spatial Frequency Filtering
Can increase or decrease brightness changes with distance
IncreasingSharpens imageIncreases noise
DecreasesBlurs imageSmoothes imageDecreases noise
Sharpening Image
Original Image Sharpened ImageNote Increased Noise
Smoothed Image
Original ImageSmoothed Image
Note Decreased Noise & Blurring
Geometric OperationsScalingSizingRotationTranslationModifies
Orientation of pixelsSpatial position of
pixels
Image Processing HardwareImage Memory
Image Processor
Digital to Analog Converter
Host Computer
Image Processing HardwareImage Memory
Temporary storage used while processing / displaying image
Image ProcessorDigital to Analog ConverterHost Computer
Image Processing HardwareImage MemoryImage Processor
Computer responsible for processing (arithmetic) done on input digital image
Digital to Analog ConverterHost Computer
Image Processing HardwareImage MemoryImage ProcessorDigital to Analog Converter
Converts output pixel values from Look-up table to analog voltage required by monitor
Host Computer
125 25 311 111 182 222 176
199 192 85 69 133 149 112
77 103 118 139 154 125 120
145 301 256 223 287 256 225
178 322 325 299 353 333 300
Image Processing HardwareImage MemoryImage ProcessorDigital to Analog ConverterHost Computer
Directs above hardwareHolds stored imagesDirects archiving