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CT Scan
By: Asadinezhad, MohsenPhD in Medical Physics
Ver:1-96
Contents Early History Tomography CT History CT Generations Spiral CT MultiSlice CT Digital Image CT Number Windowing
2
Contents Major Componemts
X-Ray Tube Beam Filtration Collimators Detectors
Image Reconstruction Image Quality
Spatial Resolution Contrast Resolution Noise
CT Radiation Dose Artifacts 3
References1. Euclid Seeram, Computed Tomography:
Principles, clinical applications and quality control, W.B.SANDERS Company
ني و كنترل كامپيوتري اصول فيزيكي، موارد استفاده بالي توموگرافيبهزادنيا، تانازياميرحسين قاسمي مهر و مترجمين، سيرام اوكليدكيفي،
جهانتابانتشارات 2. Thomas S Curry, James E Dowdey, Robert C
Murrey, Christensen's physics of diagnostic radiology
3. Matthias Hofer, CT teaching manual, THIEME4
Limitations of Radiography
Structures superimposed on film
Must view structure of interest through underlying / overlying structures
Patient
X-rayBeam
Film
5
Limitations of Radiography
Multiple views often required to adequately visualize a structure.
6
Limitations of Radiography
Optical density dictated by total attenuation encountered by beam
Thin highly-attenuating objects appear to be same density as thicker low-attenuating object.
Patient
X-rayBeam
Film
Thin denseobject
Thick lessdense object
7 8
Early Solution: Conventional Tomography
Sectional imaging methods first developed in 1920’s
9
Tomography
Body section radiography Planigraphy Stratigraphy Laminography Tomography Tomography (by ICRU in 1962)
10
Early History:Conventional Tomography
First used in 1935 Image produced on film Image plane oriented parallel to film Anatomy in plane of fulcrum stays in focus Anatomy outside of fulcrum plane mechanically blurred
11
Conventional Tomography BlurringConventional Tomography Blurring
Image produced on film
Objects above or below fulcrum plane change position on film & thus blur
Conventional Tomography Blurring
b c
12
13
Tomographic LayerTomographic Layer
⇒
S ≪ ,
2 2
2 2
S
U
2tt
b
a
V
θ
2tθ° 3 1320 6 2310 9 127 1 cm4 3132
14
Tube trajectories in Tomography
Linear Elliptical Circular Spiral Hypocycloidal Figure 8
Limitations of Conventional Tomography
Overlying / underlying structures blurred, not removed
5-10% subject contrast difference required for objects to appear different many anatomic systems do not have this subject
contrast
15
fracture of the base of the odontoid process with anterior displacement of the atlas
16
AP Projection Tomogram
TMJ
17
CT Advantages View anatomy without looking
through underlying / overlying structures improves contrast
Uses tightly collimated beam minimizes scattered radiation improves contrast
Demonstrates very small contrast differences reliable & repeatedly
CT X-rayBeam
ConventionalX-ray Beam
18
Film as a Radiation Detector
Analog not quantitative
Not sensitive enough to distinguish small differences in incident radiation
19
CT Detectors
electronic / quantitative extremely sensitive
small radiation input differences reliably & repeatedly measured & discerned
output digitized & sent to computer
20
21
How Did We Go From…
22
Conventional vs Axial Tomography
Conventional Cut
CT Axial Cut
23
Radiography vs. CT Imaging Limits of radiography / fluoroscopy
3D structures are collapsed into 2D image (obscuring of details, loss of one dimension)
Low soft-tissue contrast Not quantitative
Features of x-ray CT X-ray imaging modality (same principles of
generation, interaction, detection) Generation of a sliced view of body interior (“T”,
Tomography from Greek tomos = slice) Computational intensive image reconstruction (“C”)
24
CT Image Not produced on film Mathematically reconstructed from many
projection measurements of radiation intensity Digital Image calculated
Compu-ter
Digital Image
25
Basic principles
Mathematical principles of CT were first developed in 1917 by the Austrian mathematician Johann Radon (1887-1956)
Proved that an image of an unknown object could be produced if one had an infinite number of projections through the object
26
Basic principles
Idea popularized by a physicist (Allan Cormack) at Tufts Univ. (1963)
Allan MacLeod Cormack (1924–1998) shortly after the official announcement of the Nobel Prizes for medicine in 1979
27
CT HistoryCT History
First test images in 1967 First clinical images ~ 1971 First commercial scanner 1972
28
CT HistoryCT History CT made possible by high speed minicomputer
29
CT Computers Old mainframe computers too expensive & bulky
to be dedicated to CT
30
Godfrey Hounsfield, the English engineer developed the first CT scanner (1972) received the Nobel Prize in medicine in 1979 together with the physicist A.M. Cormack
31
Computerized Axial Tomography (CAT) Computerized Trans Axial Tomography (CTAT) Computerized Reconstruction Tomography (CRT) Digital Axial Tomography (DAT) Computed Tomography (CT)
32
Before Hounsfield and Cormack ....projection radiography, skull
33
Hounsfield: brain scan produced in 1974 with an 80 x 80 image matrix (a) and sagittal reconstruction generated from single scans taken with a spacing of 13 mm
Whole Body Scans
34
Topogram, Scout View, Scanogramor Pilot View.
35
CT Generations
37 38
First Generation (1970), Translation/Rotation, Pencil Beam
EMI Mark I (Hounsfield), pencil beam scanner (highly collimated source) excellent scatter rejection, now outdated
2 detectors 160 measurements during translation/ 180 - 240 rotation angle in steps of ~1 Used for the head (water bag fit tightly around head, Original computer
software couldn’t deal with transition from skull to air) 5-min scan time, 20-min reconstruction Original resolution: 80 80 pixels (ea. 3 3 mm2), 13-mm slice
X-ray Tube
Detector
39 40
Second Generation (1972), Translation/Rotation, Narrow Fan Beam
Narrow Fan beam (10˚) Linear detector array (~5-30 detectors) 180 ˚ rotation angle in steps of 5-10˚ Reduced number of view angles scan time ~20-30 s Slightly more complicated reconstruction algorithms because
of fan-beam projection
41
3rd Generation Geometry
Patient
42
Third Generation (1976), Rotation/Rotation, Wide Fan Beam
Wide fan beam (30-60˚) covers entire object 30-900 detectors (ionization chamber or scintillation detector) No translation required scan time ~seconds (reduced dose,
motion artifacts) Reconstruction time ~seconds Pulsed source (reduces heat load, radiation dose) Ring Artifact
43 44
4th Generation CT4th Generation CT
45
Fourth Generation (1978), Rotation/Stationary, Wide Fan Beam
Wide fan beam (30-60˚) covers entire object Stationary detector ring (600 – 4800 scintillation detectors) Rotating x-ray tube (inside or outside detector ring) Scan time, reconstruction time ~1 second Source either inside detector ring or outside (rocking, nutating
detectors)
46
Comparison of 3rd and 4th Generation
Both designs currently employed, neither can be considered superior
3rd Generation (GE, Siemens):Fewer detectors (better match, cheaper)Good scatter rejection with focused septa
4th Generation (Picker, Toshiba):Less moving partsDetectors calibrated twice per rotation
47
3rd & 4th Generation (Non-spiral) CT
Tube rotates once around patient Table stationary data for one slice collected
Table increments one slice thickness Repeat
Tube rotates opposite direction
48
Spiral CT
Patient
49
Spiral CTSpiral CT Continuous rotation of gantry & linear motion of patient
table Patient moves slowly through gantry Cables of old scanners allowed only 360o rotation (or
just a little more) Tube had to stop and reverse direction No imaging done during this time
No delay between slices Dynamic studies now limited only by tube heating
considerations Increased coverage volume / rotation
50
Slip rings - spiral CT
51
Spiral CT
table increment during one 360° rotation Pitch factor = -------------------------------------------------
slice thickness
52
Pitch factor = 1
table motion during one 360° rotation Slice Pitch = ---------------------------------------------
slice thickness
Pitch factor = 1 means slices touch each other
53
Pitch factor >1
table motion during one 360° rotation Slice Pitch = ---------------------------------------------
slice thickness
Pitch factor > 1 means gap in slices
54
Pitch factor <1
table motion during one 360° rotation Slice Pitch = ---------------------------------------------
slice thickness
Pitch factor < 1 means overlap in slices Can improve visualization of objects
55
Pitch factor = 1
equivalent dose to non-spiral
56
Pitch factor >1
lower dose for spiral if table increment per rotation > one slice thickness
57
Pitch factor <1
higher dose for spiral if table increment per rotation < one slice thickness
58
59
5th Generation: Scanners for CV Imaging – “Imatron”
No moving parts Electromagnetically swept electron beam 50 ms scan time imaging of beating heart Developed 1983 Multi slice capability
60
Cine CT (Imatron)Cine CT (Imatron) four tungsten target rings that makes a 210° arc around the patient
replaces conventional x-ray tube electron beam sweeps over each annular target ring
can be done at electronic speeds 2 detector rings with arcs of 216°
One arc with 432 detector, another with 864 detector (higher resoution) Cadmium tungstate crystal (CdWO4)
maximum scan rate 24 frames per second
Electron-beam CT, also known as fifth-generation CT
Wolbarst A B , Hendee W R Radiology 2006;238:16-39
61 62
Multi-slice CT or MultiDetector CT (MDCT) 1991
Multi-slice CT or MultiDetector CT (MDCT) 1991
Multiple rows of fan beam detectors Wider fan beam in axial direction Table moves much faster Substantially greater throughput
63
Multi-slice CTMulti-slice CT Multi-slice CT
64
Multiple detector arrays
Set of several linear detector arrays, tightly abutted
Use solid-state detector arrays Slice width is determined by the detectors, not
by the collimator (although collimator does limit the beam to the total slice thickness)
65 66
Multiple detector arrays (cont.)
3rd generation multiple detector array with 16 detectors in the slice thickness dimension and 750 detectors along each array uses 12,000 individual detector elements
4th generation scanner would require roughly 6 times as many detector elements; consequently currently planned systems use 3rd generation geometry
67
Slice thickness:single detector array scanners
Determined by the physical collimation of the incident x-ray beam with two lead jaws
Width of the detectors places an upper limit on slice thickness
For scans performed at the same kV and mAs, the number of detected x-ray photons increases linearly with slice thickness
Larger slice thicknesses yield better contrast resolution (higher SNR), but the spatial resolution in the slice thickness dimension is reduced
68
Slice thickness:multiple detector array scanners
In axial scanning (i.e., with no table movement) where, for example, four detector arrays are used, the width of the two center detector arrays almost completely dictates the thickness of the slices
For the two slices at the edges of the scan, the inner side of the slice is determined by the edge of the detector, but the outer edge is determined either by the outer edge of the detector or by the collimator penumbra, depending on collimator adjustment
69 70
Slice thickness: MDA (cont.)
In helical mode, each detector array contributes to every reconstructed image Slice sensitivity profile for each detector array needs to be
similar to reduce artifacts Typical to adjust the collimation so that the focal spot –
collimator blade penumbra falls outside the edge detectors Causes radiation dose to be a bit higher (especially for small slice
widths) Reduces artifacts by equalizing the slice sensitivity profiles
between the detector arrays
71
Detector pitch/collimator pitch
Pitch is a parameter that comes into play when helical scan protocols are used
In a helical scanner with one detector array, the pitch is determined by the collimator
Collimator pitch = table movement (mm) per 360-degree rotation of gantry / collimator width (mm) at isocenter
Pitch may range from 0.75 (overscanning) to 1.5 (faster scan time, possibly smaller volume of contrast agent)
72
Pitch (cont.)
For scanners with multiple detector arrays, collimator pitch is still valid
Detector pitch = table movement (mm) per 360-degree rotation of gantry / detector width (mm)
For a multiple detector array scanner with N detector arrays, collimator pitch = detector pitch / N
For scanners with four detector arrays, detector pitches running from 3 to 6 are used
73
Multi-detector planes
74
Multi-detector planesNew Technology
GE QXi (multi-detector CT) acquires four interweaving helices simultaneously.e.g., 4 x 5 mm slice = 20 mm total scan width
4-slice in one rotation
76
Definitions of Pitch
Old definition: Table travel per rotation
P = slice thickness
New definition:
Table travel per rotationP’=
Total nominal scan width
77
GE QXi High Quality (HQ) vs High Speed (HS)
Pitch = 15mm/20 mm =0.75
Pitch = 30mm/20 mm =1.5
20 mm
15 mm table travel
30 mm table travel
20 mm
78
79
Typical characteristics of CT
1972 1980 1990 2000
Minimum scan time 300 s 5-10 s 1-2 s 0.3-1s
Data acquired per 360° 57.6 kB 1 MB 2MB 42 MB
Data per spiral sequence - - 24-48 MB 200-500 MB
Image matrix 802 2562 5122 5122
Power (generator) 2 kW 10 kW 40 kW 60 kW
Slice thickness 13 mm 2-10 mm 1-10 mm 0.5-5 mm
Toshiba Aquilion ONE CT
80
320-slice (320 x 0.5 mm), 16cm gantry rotation, Year product introduced: 2007, 7.5 MHU, more than a $1 million
Toshiba Aquilion ONE Vision Edition
81
640-slice. 0.275 sec rotation, 16cm gantry rotation, Year product introduced: 2012
Micro CT A miniaturized design The X-rayed measuring field, usually as small as 2cm3
for material testing and analysis, medical applications are on their way to taking center stage (analysis of trabecular structures in bones)
82
Dual Energy CT Single Source or Dual Source
83
Dual Energy CT
84
Dual Source CT
85
Dual Source CT
86
Dual Source CTDetector 2 x Stellar detectorNumber of slices 2 x 128Rotation time 0.28 s‐1
Temporal resolution 75 ms-1, heart-rate independentGenerator power 200 kW (2 x 100 kW)kV steps 70, 80, 100, 120, 140 kVIsotropic resolution 0.33 mmCross-plane resolution 0.30 mmMax. scan speed 458 mm/s1 with Flash SpiralTable load up to 307 kgGantry opening 78 cm
87
SPECT-CT
88
SPECT-CT
89
PET-CT
90
PET-CT
4D PET-CT Image
91
PE
T-C
T
92
93
Measure Intensity of a Pencil Beam
X-Ray Source
Radiation Detector
94
Principle of X-Ray CT
In one plane, obtain set of line integrals for multiple view angles
Reconstruct cross-sectional views
Detector
Linear scan
Angular scan
Object
95
Pixels & Voxels
96
Digital ImageDigital Image
2-dimensional array of individual image points calculated
each point called a pixel picture element
each pixel has a value value represents x-ray
transmission (attenuation)
97
Pixels & Voxels
Pixel is 2D component of an image
Voxel is 3D cube of anatomyVolume Element
CT reconstruction calculates attenuation coefficients of Voxels
CT displays CT numbers of Pixels as gray shades
98
Pixel & Voxel Size
Voxel depth same as slice thickness
Pixel dimension field of view / matrix size
FOV = 30 cm256 pixels 30 cmPixel size = ------------
256 pixels
Pixel size = 0.117 cm = 1.17 mm
99
Attenuation Equation forMono-energetic Photon Beams
I = Ioe-x
I = Exiting beam intensityIo = Incident beam intensitye = constant (2.718…) = linear attenuation coefficient
•property of•absorber material•beam energy
x = absorber thickness
MaterialIo
I
x
For photons which are neither absorbed nor scattered
100
Example Beam Attenuation
Using equation to calculate beam intensity for various absorber thicknesses ( = .223)
1cm100 80
I = Ioe-x
100*e-(0.223)(1) = 80-20%
101
Example Beam Attenuation
Using equation to calculate beam intensity for various absorber thicknesses ( = .223)
1cm 1cm100 80 64
I = Ioe-x
100*e-(0.223)(2) = 64
-20% -20%
102
Example Beam Attenuation
Using equation to calculate beam intensity for various absorber thicknesses ( = .223)
1cm 1cm 1cm100 80 64 51
I = Ioe-x
100*e-(0.223)(3) = 51
-20% -20% -20%
103
Example Beam Attenuation
Using equation to calculate beam intensity for various absorber thicknesses ( = .223)
1cm 1cm 1cm 1cm100 80 64 51 41
I = Ioe-x
100*e-(0.223)(4) = 41
-20% -20% -20% -20%
104
More Realistic CT Example Beam Attenuation for non-uniform Material 4 different materials 4 different attenuation coefficients
#1 #2 #3 #4
1 2 4
Io I
x
I = Ioe-(+++)x
105 106
Reconstruction:Solve for ’s
16 22 11 1017
22
12
10
15
13
11 12 13 14
21 22 23 24
31 32 33 34
41 42 43 44
107
Real Problem Slightly More Complex
11 12 13 14
21 22 23 24
31 32 33 34
41 42 43 44
24 13 15 22 16
35
13
22
9
14512 values
512values
108
Effect of Beam Energy on Attenuation
Low energy photons more easily absorbed High energy photons more penetrating All materials attenuate a larger fraction of low
than high energy photons
Material100 80
Higher-energymono-energeticbeam
30Material
Lower-energymono-energeticbeam
100
109
Mono vs. Poly-energetic X-ray Beam Equations below assume Mono-energetic x-
ray beam
#1 #2 #3 #4
1 2 4
Io I
x
I = Ioe-(+++)xI = Ioe-x110
Mono-energetic X-ray Beams
Available from radionuclide sources Not used in CT because beam intensity much
lower than that of an x-ray tube
111
X-ray Tube Beam High intensity Produces poly-energetic beam
#1 #2 #3 #4
1 2 4
Io I
x
I = Ioe-(+++)xMono-energetic beam equation!
112
Beam Hardening Complication Attenuation coefficients n depend on beam energy!!! Beam energy incident on each block unknown Four ’s, each for a different & unknown energy
1 2 4
1cm 1cm 1cm 1cm
I = Ioe-(+++)x
113
Beam Hardening Complication
Beam quality changes as it travels through absorber greater fraction of low-energy photons removed from
beam Average beam energy increases
1cm 1cm 1cm 1cm
Fewer PhotonsBut higher avg
kV than A
Fewer PhotonsBut higher avg
kV than B
A B
Fewer PhotonsBut higher avg
kV than C
C D
Fewer PhotonsBut higher avg
kV than D
E
114
Reconstruction
Scanner measures “I” for thousands of pencil beam projections
Computer calculates tens of thousands of attenuation coefficients one for each pixel
Computer must correct for beam hardening effect of increase in average beam energy from one side of
projection to other
I = Ioe-(++++)x
115
CT Number (The Hounsfield Unit)
Calculated from reconstructed pixel attenuation coefficient
t - W)HU= CT # = 1000 ------------
W
Where:t = linear attenuation coefficient for tissue in pixelW = linear attenuation coefficient for water
Caculate CT # for Water. Answer: 0Caculate CT # for Air. Answer: -1000
116
CT Numbers for Special Stuff
Bone: +1000 Water: 0 Air: -1000
t - W)CT # = 1000 ------------
W
117
The Hounsfield scale
118
Digital Image MatrixDigital Image Matrix
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
119
Numbers / Gray ShadesNumbers / Gray Shades
Each number of a digital image corresponds to a gray shade for one pixel
120
Digital to Analog Conversion(D to A)
Computer reconstructs digital image set of numbers
Computer displays analog image
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
121
Analog vs. Digital Images
Analog continuous gray
shade information Digital
Discrete gray shade information
122
Digital Image FormationDigital Image Formation
Clinical ImageScreen Wire Mesh
123
Digital Image Formation:Sampling
Digital Image Formation:Sampling
Place mesh over image
Assign each square (pixel) a value based on density
Pixel values form the digital image
120
-10
-650
124
Digital Image Formation:Sampling
Digital Image Formation:Sampling
Each pixel assigned a value
Value averages entire pixelAny spatial variation
within a pixel is lostThe larger the pixel,
the more variation120
-10
-650
125
Digital Image FormationDigital Image Formation The finer the mesh (sampling), the more accurate the
digital rendering
126
What is this?What is this?
12 X 9 Matrix
127
Same object, smaller squaresSame object, smaller squares
24 X 18 Matrix128
Same object, smaller squaresSame object, smaller squares
48 X 36 Matrix
129
Same object, smaller squaresSame object, smaller squares
96 X 72 Matrix 130
Same object, smaller squaresSame object, smaller squares
192 X 144 Matrix
131
Image Reconstruction
AcmeMini-
Computer
Projection(raw)Data
Pixel(calculated)
Data
X-Ray Source
Radiation Detector
132
Data AcquisitionData Acquisition
cross sectional image reconstructed from many straight line transmission measurements made in different directions
Tube
Detector
133
Projection MeasurementsProjection Measurements
Radiation detector generates a voltage proportional to radiation intensity
134
Image Reconstruction Minicomputer does its thing
Analog to Digital (A to D) conversion
135
Digital Image MatrixDigital Image Matrix
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 Matrix contains many numbers which may be Displayed on CRT Manipulated Stored
136
Image Reconstruction
One of these equations for every projection line
IA = Ioe-(++++)xProjection #A
IC = Ioe-(C+C+C+C+)xProjection #C
Projection #B
IB = Ioe-(++++)x
137
Image Reconstruction
IA = Ioe-(++++)x
IB = Ioe-(++++)x
IC = Ioe-(C+C+C+C+)x
Projection #A
Projection #B
Projection #C
IA, IB, IC, ...What We Measure:
A1, A2, A3, ...
Reconstruction Calculates:
B1, B2, B3, ...C1, C2, C3, ...
Etc. 138
Display & WindowingDisplay & Windowing
Gray shade assigned to each pixel value (CT #)
Windowing Assignment of display brightness to pixel
values does not disturb original pixel values in
memory Operator controllable
Window Width Window Level
47
93
139
Display & Display Matrix:Resolution
CT images usually 512 X 512 pixels Display resolution better
often 1024 X 1024 can be as high as 2048 X 2048
$$$
140
Display & Display Matrix:Contrast
CT #range -1000 to 3000
Monitor can display far fewer gray shades Eye can discern few gray shades Purpose of Window & Leveling
display only portion of CT # values Emphasize only those CT #’s display of CT #’s above & below window all black OR all white
141
Pixel Values & Gray Shades
# of valid pixel values depends on bit depth 1 bit: 2 values 2 bits: 4 values 3 bits: 8 values 8 bits: 256 values 10 bits: 1024 values n bits: 2n values
142
Pixel Values & Gray Shades
CT can discern ~ 4000 gray shades Typical bit depth: 10 bits = 1024 gray shades Single gray shade represents range of pixel
values
143
Window Width & Level
Window width range of CT #’s imaged determines maximum # of gray
shades which could be displayed on CRT
Window level center or midpoint of CT # range
144
Window Width & Level
Pixels outside of window displayed as Black or White
145
Window Width & Level
>200
151-200
101-150
51-100
1-50
(-49)-0
(-99)-(-50)
(-149)-(-100)
(-199)-(-150)
<(-199)
3000
0
1000
2000
Window: 400Level: 0
-1000146
Small Window Width200
-200
0
1000
-1000
Window: 400Level: 0
� Short gray scale� Small block of CT #’s
assigned gray levels� Small transition zone
of white to black
147
Small Window Width200
-200
0
1000
-1000
Window: 400Level: 0
� Used to display soft tissues within structures containing different tissues of similar densities
� Level centered near average CT # of organ of interest
148
Large Window Width
0
1000
Window: 2000
Level: 0
-1000
� Long gray scale� Large block of CT #’s
assigned gray levels� Large transition zone of
white to black
149
Large Window Width
0
1000
Window: 2000
Level: 0
-1000
� Used where large latitude required
� Used to simultaneously display tissues of greatly differing attenuation
150
Window Example
WL =0WW = 200
All pixels with CT #’s > 0 +(200/2) = 100: White
All pixels with CT #’s < 0 -(200/2) = -100: Black
100
-100
200 0
151
Another Window Example
WL = 40WW = 200
All pixels with CT #’s > 40 + (200/2) = 140: White
All pixels with CT #’s < 40 - (200/2) = -60: Black
140
-60
200 40
152
Still Another Window Example
WL = 0WW = 400
All pixels with CT #’s > 0 + (400/2) = 200: White
All pixels with CT #’s < 0 - (400/2) = -200: Black
200
-200
400 0
153
Larger Window Means Obscuring Small Differences in Tissue Attenuation
One gray shade encompasses larger range of CT #’s
200
-200-100
100
20 - 40 40 - 8020 40
WW=200 WW=400
Range
154
Windowing procedures to display CT images. The diagnostically relevant range of CT values is selected by choosing the center and width (C/W) of the window.
155
Window Width & Contrast
As WW increases contrast decreases latitude (range of CT #’s
imaged) increases As WW decreases
contrast increases latitude decreases
Clinical goal: Largest available contrast at
the latitude required by study
156
Window Width & Image Contrast
Large window width different structures more likely to have same
gray shade Narrow window width
Gray shade differences more likely visible between structures
Very narrow window width Small differences in attenuation seen as black
& white
157
Preset Window & Level
Available for all commercial CT initial WW and WL pre-sets for specific study
types Can be overridden by operator
158
Silly CT # Display Example:10 Gray Shades
>700
651-700
601-650
551-600
501-550
451-500
401-450
351-400
301-350
<301
159
CT # Level Change
Darks lighterlights lighter
Decreased LevelConstant Window
160
CT # Level Change
>700
651-700
601-650
551-600
501-550
451-500
401-450
351-400
301-350
<301
>200
151-200
101-150
51-100
1-50
(-49)-0
(-99)-(-50)
(-149)-(-100)
(-199)-(-150)
<(-199)
161
CT # Level Change
>700
651-700
601-650
551-600
501-550
451-500
401-450
351-400
301-350
<301
>200
151-200
101-150
51-100
1-50
(-49)-0
(-99)-(-50)
(-149)-(-100)
(-199)-(-150)
<(-199)
3000
-1000
0
1000
2000
Window: 400Level: 500
Window: 400Level: 0
162
CT # Window Change
Darks lighter,lights darker
163
CT # Window Change
>700
651-700
601-650
551-600
501-550
451-500
401-450
351-400
301-350
<301
>900
801-900
701-800
601-700
501-600
401-500
301-400
201-300
101-200
<101164
CT # Window Change
>700
651-700
601-650
551-600
501-550
451-500
401-450
351-400
301-350
<301
3000
-1000
0
1000
2000
>900
801-900
701-800
601-700
501-600
401-500
301-400
201-300
101-200
<101
Window: 800Level: 500
Window: 400Level: 500
165 166
Major Components
Scanner Room Imaging system Generator (?)
Electronics Room Power Computer (?) Generator (?)
Operator’s Area Display / recording / storage Computer (?)
167
Major Components
X-Ray Production
X-Ray Detection
Computer Systems
Reconstruction
X-Ray Tube
Detectors
A - D Conversion
Display & Format
Printing
Archiving
Generator
168
Major Components
The Gantry X Ray Tube, Detectors, H.V Generator
The Operating Console Operator Console
kV, mA, Slice Thickness
Physician Console The Computer
169
X-Ray System Components
X-Ray Generator X-Ray Tube Beam Filter Collimators
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X-Ray Generator
3 phase originally used Most vendors now use high frequency generators
relatively small small enough to rotate with x-ray tube can fit inside gantry
lower ripple than 3 phase more efficient production of x-rays
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X-Ray Tube
Must provide sufficient intensity of transmitted radiation to detectors
Radiation incident on detector depends upon beam intensity from tube patient attenuation
beam’s energy spectrum patient
thickness atomic # Density
500,000 to 2,000,000 HU172
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Patient
CT Beam Filtration
Hardens beam preferentially removes low-
energy radiation Removes greater fraction of low-
energy photons than high energy photons
reduces patient exposure Attempts to produce uniform
intensity & beam hardening across beam cross section
Filter
CT Beam Filtration
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Filter
Collimators
Source Detector
Pre-Collimator Post-Collimator
Patient
Scattering
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Tube, collimator & detector
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Pre-Collimation
Constrains size of beam Reduces amount of scatter produced Designed to minimize beam divergence Often consists of several stages or sets of jaws
Tube
Detector
Pre-collimator
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Post-Collimation
Helps define slice (beam) thickness Reduces scatter radiation reaching detector
Tube
Detector
Post-collimator
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CT Detector Technology:Desirable Characteristics
High efficiency Quick response time High dynamic range Stability
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CT Detector EfficiencyDefinition
Ability to absorb & convert x-ray photons to electrical signals
181
Efficiency Components
Capture efficiency fraction of beam incident on active detector
Absorption efficiency fraction of photons incident on the detector which are
absorbed Conversion efficiency
fraction of absorbed energy which produce signal
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Overall Detector Efficiency
Overall detector efficiency =
capture effi. × absorption effi. × conversion effi.
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Absorption Efficiency
Depends upon detector’s atomic # density size thickness
Depends on beam spectrum
capture efficiency×
absorption efficiency×
conversion efficiency
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Response Time
Minimum time after detection of 1st event when detector can detect 2nd event
If time between events shorter than response time, second event may not be detected
Shorter response time better
185
Stability
“Steadiness” of detector system
Consistency of detector signal over time
The less stable, the more frequently calibration required
186
Dynamic Range
Ability to faithfully detect large range of intensities
Ratio of largest to smallest signal which can be faithfully detected
Typical dynamic range: 1,000,000:1 much better than film
Detector Types: Gas Ionization Measurement of conductivity induced in a gas volume by the
ionizing effect of x-rays. X-rays ionize gas molecules Ions are drawn to electrodes by electric field
Number of ion pairs N produced x-ray intensity
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++ + +-- - -
+ -
Ammeter
Anode
Cathode
Collimator
Gas Ionization Chambers CharacteristicsTo optimize efficiency usually filled with Xenon (high Z) under pressure (up to 30 atm) Cheap Excellent stability Large dynamic range High spatial resolution Low efficiency
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Detector Types: Scintillation
X-ray energy converted to light Light converted to electrical signal
X-Rays
Photomultiplier Tube
Light
ElectricalSignal
ScintillationCrystal
Scintillation materials: NaI(Tl), BGO PMTCdWO4, CsI, Rare Earth Oxides (Gd2O2S) PD
•Scintillation material thick enough to provide quantum efficiency ~ 100% 190
Photomultiplier Tubes
Light incident on Photocathode of PM tube Photocathode releases electrons
X-Rays Light
ScintillationCrystal PM
TubePhotocathode
-+
Dynodes
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Photomultiplier Tubes
Electrons attracted to series of dynodes each dynode slightly more positive than last one
X-Rays Light
ScintillationCrystal PM
TubePhotocathode
-+
+
+
+
+
Dynodes
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Photodiode
Made of two types of materials p-type n-type
Lens focuses light from crystal onto junction of p & n type materials
pn
Lens JunctionX-Rays Light
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Photodiode
Light controls resistance of junction Semiconductor current proportional to light
falling on junction
pn
LensJunctionX-Rays Light
194
Solid State Detectors Output electrical signal amplified Fast response time Large dynamic range Almost 100% conversion & photon capture
efficiency
Factors Affecting Detector Signal
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kV: high kV x-rays more penetrating mA: high tube current gives more intense x-
ray beam Scan time: long scan time more x-rays to
detectors Slice thickness: wide slice more x-rays Patient composition: small patients less
attenuating
Image Reconstruction
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“It All Adds Up” Puzzle
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“It All Adds Up” Puzzle
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This is what your CT Scanner must solve!
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Reconstruction:Solve for ’s
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Real Problem Slightly More Complex
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14512 values
512values
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Real Reconstruction Problem
� Intensity (transmission) measured
� Rays transmitted through multiple pixels
� Find individual pixel values from transmission data (question marks)
? ? ? ?? ?
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? ? ? ?? ? 534
417
364
555
501
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255 712199
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Raw Data� unanalyzed data;
data not yet subjected to analysis
� Intensity (transmission) measurements for each ray for each projection
534
417
364
501
255 712199
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Image Data� Individual pixel
values (question marks)
? ? ? ?? ?
? ? ? ?? ?
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Algorithm� Set of rules for getting a specific output (answer)
from a specific input� Basic Reconstruction algorithm methods
1. Back Projection پس نمايش 2. Iterative method روش تكرار شونده 3. Analytical Method روشهاي تحليلي
205
� ALSO CALLED SUMMATION METHOD OR LINEAR SUPERPOSITION METHOD
� Reverse the process of measurement of projection data to reconstruct an image
Back Projection ReconstructionBack Projection Reconstruction
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Back Projection ReconstructionBack Projection Reconstruction
� Back Projection• for given projection,
assume equal attenuation for each pixel
• repeat for each projection adding results
9999999 9
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Back Projection ReconstructionBack Projection Reconstruction
� Reconstruction Problem• converting transmission data for
individual projections into attenuation data for each pixel
??????? 9
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Back Projection ReconstructionBack Projection Reconstruction
� Assume actual image has 1 hot spot (attenuator)
� Each ray passing through spot will have attenuation back-projected along entire line
� Each ray missing spot will have 0’s back-projected along entire line
Hot Spot
9999999 9
0000000 0209
Back Projection ReconstructionBack Projection Reconstruction
� Each ray missing spot stays blank� Each ray through spot shares some density
• Location of spot appears brightest
Hot Spot
9999999 9
0000000 0
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Back Projection ReconstructionBack Projection Reconstruction
HotSpot
Star Artifact Spokes
� Streaks appears radially from spot• star artifact
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Back Projection ReconstructionBack Projection Reconstruction
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Back Projection ReconstructionBack Projection Reconstruction
:معايب اين روش�.تصوير هر نقطه به شكل ستاره در مي آيد1..دقت تصوير بسيار پائين است2..تصوير مقدار زيادي نويز زمينه يا مه آلودگي دارد3..كنتراست تصوير پائين است4.
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Iterative methods روشهاي تكرار شونده Based on a series of estimates and corrections for errorsITERATIVE TECHNIQUES ARE NOT USED IN TODAY’S
COMMERCIAL SCANNERS1. Simultaneous Correction تصحيح همزماني
or Iterative Least Square Technique (ILST)روش بازسازي تصوير با حداقل كردن خطاهاي مربعها
2. Ray by Ray Correction تصحيح اشعه به اشعهor Algebra Reconstruction Technique (ART)روش بازسازي جبري
3. Point by Point Correction تصحيح نقطه به نقطهor Simultaneous Iterative Reconstruction Technique (SIRT)روش بازسازي تصحيح همزمان
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Iterative ReconstructionIterative Reconstruction� Start with measured data
? ? ?
? ? ?
? ? ?
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Measurements
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Iterative ReconstructionIterative Reconstruction� Make initial guess for first projections
by assuming equal attenuation for each pixel in a projection
� Similar to back projection
8 4 4
8 4 4
8 4 4
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Initial guess basedupon vertical projections
Measurements
? ? ?
? ? ?
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Measurements
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Iterative ReconstructionIterative Reconstruction
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Iterative ReconstructionIterative Reconstruction
� changing pixels for one projection alters previously-calculated attenuation for others
� corrections repeated for all projections until no significant change / improvement
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Iteration Image ReconstructionIteration Image Reconstruction
� operationally slow and cumbersome, even for computers
� not used
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:معايب اين روش�ه زمان نسبتاً طوالني جهت اجراي هر تكرار و در نتيج1.
بازسازي تصويررائب احتمال تفاوت ضرائب تضعيف محاسبه شده با ض2.
حقيقي
Iteration Image ReconstructionIteration Image Reconstruction
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Analytical Methods روشهاي تحليليUSED IN MODERN CT SCANNERS Developed to overcome
limitations of back-projection and iterative algorithms1. Filtered Back Projection پس نمايش فيلتر شده2. Fourier Analysis آناليز فوريه
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Filtered Back ProjectionFiltered Back Projection� enhancement of back projection
technique� filtering function (convolution)
is imposed on transmission data• small negative side lobes placed
on each side of actual positive data
• negative values tend to cancel star artifact
Filtered back
projection
Unfiltered back
projection
*
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Filtered Back ProjectionFiltered Back ProjectionSTEPS IN FILTERED BACK PROJECTION:� ALL PROJECTION PROFILES ARE OBTAINED � THE LOGARITHM OF DATA IS OBTAINED � LOGARITHMIC VALUES ARE MULTIPLIED BY DIGITAL
FILTER � FILTERED PROFILES ARE BACKPROJECTED � THE FILTERED PROJECTIONS ARE SUMMED AND THE
NEGATIVE AND POSITIVE COMPONENTS ARE CANCELLED
* Filtered Back ProjectionFiltered Back Projection� operationally fast
• reconstruction begins upon reception of first transmission data
� best filter functions found by trial & error
� Most common commercial reconstruction algorithm
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Filtered Back ProjectionFiltered Back Projection
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Filtered Back ProjectionFiltered Back Projection
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Fourier Analysis� USED IN MRI, NOT USED IN CT BECAUSE OF COMPLICATED
MATHEMATICS
� converts data from spatial domain to frequency domain• breaks any signal into frequency component
parts
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Multi-plane reconstructionMulti-plane reconstruction� Or Multiplanar Reformatting� using data from multiple axial
slices it is possible to obtain• sagittal & coronal planes• oblique & 3D reconstruction
� Non-spiral reconstruction• Poor appearance if slice thickness
>>pixel size • isotropic imaging
� multi-plane reconstructions are computer intensive (Can be slow) 228
Saggital / Coronal Reconstructions
Saggital
Coronal
Axial
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3D Reconstructions
230
3D Reconstructions� Uses pixel data from multiple slices� Algorithm identifies surfaces & volumes� Display renders surfaces & volumes
• Three Dimensional Shaded Surface• Volume Rendering• Maximum Intensity Projection (MIP)
� Real-time motion» auto-rotation» user-controlled multi-plane rotation
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Interpolation� Calculating attenuation data for specific slice
from spiral raw data� Table moves continually� As tube rotates table constantly moves
Position at start of rotation
Position at start of rotation
Position of interest 232
Interpolation
� Estimates value of function using known values on either side
When x = 50, y = 311When x = 80, y = 500
What will be the value of y when x=58? (50,311)
(80,500)?
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Interpolation� 58 is 8/30ths of the way between points� “y” when x=58 will be 8/30ths of the way
between 311 and 500
(50,311)
(80,500)?
58
?=311+8/30 (500-311)
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Three Dimensional Shaded Surface1. User selects a threshold range2. The voxels with CT# within the
threshold range are set to the "on" state, The rest of the voxels are set to the "off“ state
3. Project rays through the entire volume4. As the rays pass through the data, they
stop when they identify the first "on" voxel (part of the surface); the other voxels are ignored.
5. This is done for all the rays� No details below the surface 235
Volume Rendering� Displays an entire volume set with control of the opacity or
translucency of selected tissue types� Each voxel has an associated intensity in addition to an
associated opacity value
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Maximum Intensity Projection (MIP)� easy viewing of vascular structures or air-filled cavities� The rays are cast throughout the volume, and depending on
whether it is maximum intensity projection or minimum intensity projection, maximum or minimum values along the rays are used in the final image display.
� preferred method for many CT angiography applications because visualization of contrast-filled vasculature is fast and easy.
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CT Image Quality Parameters
SpatialResolution
ImageNoise
ContrastResolution
Artifacts
CTاطالعات آناتوميكي مهم در روي تصوير ) تشخيص(قابل رويت بودن
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Factors InfluencingCT Image Quality
BeamCharacteristics
Patient Dose
SliceThickness
Scatter
DisplayResolution
ReconstructionAlgorithm
SubjectTransmissivity
QUALITY MEASUREMENT METHODS
� PSF- POINT SPREAD FUNCTION � LSF- LINE SPREAD FUNCTION � CTF – CONTRAST SPREAD FUNCTION � MTF- MODULATION TRANSFER
FUNCTION � ERF- Edge Response Function
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PSF- POINT SPREAD FUNCTION
� Describes the lack of sharpness that results when a point in the object is not reproduced as a “true” point in the image. As a result this causes blurring
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Full width at half-maximum (FWHM)
LSF- LINE SPREAD FUNCTION
� Also describes the unsharpness of an imaging system when a line or slit object is not reproduced as a line or slit but instead spreads out as a measurable distance.
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CTF – CONTRAST SPREAD FUNCTION
� Also Known As the contrast response function measures the contrast response of an imaging system. When utilizing a phantom/test pattern it is the resultant difference in density between the adjacent regions of the slits.
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MTF MODULATION TRANSFER FUNCTION
� The MTF is a combination of LSF, PSF and ERF. It is obtained with the Fourier transform of the LSF, PSF, and ERF.
� MOST COMMONLY USED TO DESCRIBE SPATIAL RESOLUTION IN CT.
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MTF
� MTF OF 1 – 100% TRANSFER OF OBJECT TO IMAGE
� MTF OF 0 – 0% TRANSFER OF OBJECT TO IMAGE
Spatial frequency
Lp/cm
Spatial Frequency
� LARGE OBJECTS – LOW S.F.
� SMALL OBJECTS – HIGH S.F.
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SPATIAL FREQUENCY� Smallest resolvable high contrast object� Often expressed as line pairs / cm� “Pair” is one object + one space
OnePair
SPATIAL FREQUENCY
1
3
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SPATIAL FREQUENCY� Smallest resolvable high contrast object is
half the reciprocal of spatial frequency� Example:
• Limited resolution = 15 line pairs per cm• Pair is 1/15th cm• Object is half of pair
» 1/15th / 2» 1/30th cm» .033 cm» 0.33 mm
1/15th cm
1/30th cm
Resolution in CT
Spatial Resolution Contrast Resolution
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Spatial Resolution� Quantifies image blurring� “Ability to discriminate objects of varying density a
small distance apart against a uniform background”� Minimum separation required between two high
contrast objects for them to be resolved as twoobjects
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Factors affectingSpatial Resolution (↑)
� Focal spot size (↓)� Detector aperture width (↓)� FOV (↓) Pixel Size (↓)� Slice Thickness or collimation (↓)
• Less variation likely for thinner slices• attenuation variations within a voxel are averaged
» partial volume effect
� Voxel Size (↓): Pixel Size & Slice Thickness� Patient Movement (↓)� Reconstruction algorithms (Bone filters have the best spatial
resolution, and soft tissue filters have lower spatial resolution)• smoothing or enhancing of edges
� Greater pitches reduce resolution
� CT spatial resolution phantom, consisting of 4–12 line-pairs per centimeter, reconstructed using standard (A) and bone (B, high-resolution) filters.
255 256
Hi-Resolution CT (HRCT) Technique� Very small slice thicknesses
• 1-2 mm� High spatial frequency algorithms
• increases resolution» increases noise» Noise can be offset by using higher doses
� Optimized window / level settings� Small field of view (FOV)
• Known as “targeting”
257
Contrast Resolution
� Ability of an imaging system to demonstrate small changes in tissue contrast
� The difference in contrast necessary to resolve 2 large areas in image as separate structures
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Contrast ResolutionContrast Resolution
� Difference in x-ray attenuation required for 2 pixels to be assigned different digital values
89
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Image Contrast
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� Contrast = difference in signal = difference in CT number between an object and the surrounding tissue
� = CT # B - CT # A
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Image quality� C.RCT > C.RR� S.RCT< S.RR� Limiting spatial resolution for screen-film
radiography is about 7 lp/mm; for CT it is about 0.5 – 1.5 lp/mm
� Contrast resolution of screen-film radiography is about 5%; for CT it is about 0.5%
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Factors affecting Contrast Resolution (↑)
� Noise (↓)� Voxel Size (↑): Pixel Size & Slice Thickness� kVp (↑)� Patient Movement (↓)� Reconstruction algorithms: (Bone filters
produce lower contrast resolution, and soft tissue filters improve contrast resolution)
CT Contrast Resolution Depends on Noise
� (A and B) Comparison of noise from scans using 270 mAs (typical clinical value) and 100 mAs.
� (C) Appearance of image noise is strongly affected by reconstruction filter; sharp filter such as bone also sharpens (enhances) appearance of noise. 262
263
CT Contrast Resolution Depends on NoiseImage Noise
� 120 kVp, 1.25mm, 0.5 sec
� 640 mA 25mA264
265
Small Contrast Difference Harder to Identify in Presence of Noise
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CT Contrast Resolution
Contrast depends on noise
Noise depends on # photons detected
# photons detected depends on …
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# of Photons Detected Depends Upon
� photon flux (x-ray technique)� slice thickness� patient size� Detector efficiency� Note:
• Good contrast resolution requires that detector sensitivity be capable of discriminating small differences in intensity
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CT Image Noise� Fluctuation of CT
#’s in an image of uniform material (water)
� Usually described as standard deviation of pixel values
Image Noise� Variation in CT number in image of a uniform object
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CT Image Noise
� Standard deviation of pixel values
S(xi - xmean)2
Noise (s) = -------------------(n-1)
Xi = individual pixel valueXmean = average of all pixel values in ROIn = total # pixels in ROI
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Noise Level� Units
• CT numbers (HU’s)or
• % contrast
� Example• CT # range: 1000 HU’s• Standard deviation: 3 HU’s• Noise level is 3 or 3 / 1000 X 100 = 0.3%
272
CT Noise Levels Depend Upon
# detected photonsquantum noise
matrix size (pixel size) slice thickness algorithm electronic noise scattered radiation object size Photon flux to
detectors…
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Photon Flux to Detectors
� Tube output flux (intensity) depends upon• kVp• mAs• beam filtration
� Flux is combination of beam quality & quantity
� Flux to detectors modified by patient
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Slice Thickness� Thinner slices mean
• less scatter» better contrast
• less active detector area» less photons detected» More noise
� To achieve equivalent noise with thinner slices, dose (technique factors) must be increased
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Noise Levels in CT:� Increasing slice thickness degrades spatial
resolution• less uniformity inside a larger pixel• partial volume effect
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Noise Levels in CT:� When dose increases, noise decreases
• dose increases # detected photons� Doubling spatial resolution (2X lp/mm)
requires an 8X increase in dose for equivalent noise• Smaller voxels mean less radiation per voxel
CT Radiation Doses
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CT Radiation Doses
• Well-established relationship among SNR, pixel dimensions (), slice thickness (T), and radiation dose (D):
Artifacts in CT Imagesany systematic discrepancy between the CT numbers in the reconstructed image and the
true attenuation coefficients of the object
Artifacts in CT Images
• Artifacts can seriously degrade the quality of computed tomographic (CT) images, sometimes to the point of making them diagnostically unusable. To optimize image quality, it is necessary to understand why artifacts occur and how they can be prevented or suppressed.
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Artifacts in CT Images
• CT artifacts originate from a range of sources.
1. Physics-based artifacts2. Patient-based artifacts3. Scanner-based artifacts4. Helical and multi section technique
artifacts
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1. Physics-based artifacts
result from the physical processes involved in the acquisition of CT data
a. Beam Hardeninga. Cupping Artifactsb. Streaks and Dark Bands
b. Partial Volume
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Beam Hardening
• As the beam passes through an object, it becomes “harder” , that is to say its mean energy increases, because the lower energy photons are absorbed more rapidly than the higher-energy photons
283
Beam Hardening
Changing energy spectrum of an x-ray beam as it passes through waterThe mean energy increases with depth(The attenuated spectra have been rescaled to be equivalent in size to the unattenuated spectra.)
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285
Because the attenuation of bone is greater than that of soft tissue, bone causes more beam hardening than an equivalent thickness of soft tissue
Beam Hardening
Two types of artifact can result from this effect:
• cupping artifacts • the appearance of dark bands or
streaks between dense objects in the image
286
Cupping Artifacts• X rays passing through
the middle portion of a uniform cylindrical phantom are hardened more than those passing though the edges because they are passing though more material.
287
Cupping Artifacts
288
CT number profiles obtained across the center of a uniform water phantom
Streaks and Dark Bands• In very heterogeneous cross sections, dark
bands or streaks can appear between two dense objects in an image. They occur because the portion of the beam that passes through one of the objects at certain tube positions is hardened less than when it passes through both objects at other tube positions. This type of artifact can occur both in bony regions of the body and in scans where a contrast medium has been used
289
Streaks and Dark Bands
290
CT image shows streaking artifacts due to the beam hardening effects of contrast medium.
Minimizing Beam Hardening
• Filtration• Higher kVp• calibration correction• beam hardening correction software
291292
Filtration
• A flat piece of attenuating, usually metallic material is used to “pre-harden” the beam by filtering out the lower-energy components before it passes through the patient. An additional “bowtie” filter further hardens the edges of the beam, which will pass through the thinner parts of the patient.
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Calibration correction
• Manufacturers calibrate their scanners using phantoms in a range of sizes. This allows the detectors to be calibrated with compensation tailored for the beam hardening effects of different parts of the patient.
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Calibration correction of Cupping Artifacts
295
CT number profiles obtained across the center of a uniform water phantom without calibration correction (a) and with calibration correction (b).
Calibration correction of Cupping Artifacts
• Since patient anatomy never exactly matches a cylindrical calibration phantom, in clinical practice there may be either a slight residual cupping artifact or a slight “capping” artifact, with a higher central CT value due to overcorrection.
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Beam hardening correction software
• An iterative correction algorithm may be applied when images of bony regions are being reconstructed
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Beam hardening correction software
298
dark banding that occurs between dense objects when only calibration correction is applied (a) and the reduction in artifacts when iterative beam hardening correction is also applied (b)
Avoidance of Beam Hardening by the Operator
• It is sometimes possible to avoid scanning bony regions, either by means of patient positioningor by tilting the gantry
• It is important to select the appropriate scan field of view to ensure that the scanner uses the correct calibration and beam hardening correction data and, on some systems, the appropriate bowtie filter.
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Partial Volume• CT #’s based on linear attenuation coefficient for
tissue voxels• If voxel non-uniform (contains several materials),
detection process will average• Can appear as
incorrect densitiesstreaksbands
• MinimizingUse thinner slicesSoftware compensation
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2. Patient-based artifacts
are caused by such factors as patient movement or the presence of metallic materials in or on the patient.
a. Metallic Materialsb. Patient Motionc. Incomplete Projections
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Metallic Materials
• Can lead to severe streaking artifacts• They occur because the density of the
metal is beyond the normal range that can be handled by the computer, resulting in incomplete attenuation profiles
304
Avoidance of Metal Artifacts by the Operator
• Patients are normally asked to take off removable metal objects such as jewelry
• For non removable items, such as dental fillings, prosthetic devices, and surgical clips, it is sometimes possible to use gantry angulation to exclude the metal inserts from scans of nearby anatomy
• When it is impossible to scan the required anatomy without including metal objects, increasing technique, especially kilovoltage, may help penetrate some objects, and using thin sections will reduce the contribution due to partial volume artifact
305
Software Corrections for Metal Artifacts
• Manufacturers use a variety of interpolation techniques to substitute the overrange values in attenuation profiles
306
Software Corrections for Metal Artifacts
307
CT images of a patient with metal spine implants, reconstructed without any correction (a) and with metal artifact reduction (b)
Patient Motion
• Patient motion can cause misregistration artifacts, which usually appear as shading or streaking in the reconstructed image.
• Steps can be taken to prevent voluntary motion, but some involuntary motion may be unavoidable during body scanning.
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309
Patient Motion• Small motions cause image blurring• Larger physical displacements produce
artifacts that appear as double images or image ghosting
Patient Motion
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Avoidance of Motion Artifacts by the Operator
• The use of positioning aids is sufficient to prevent voluntary movement in most patients.
• in some cases (eg, pediatric patients), it may be necessary to immobilize the patient by means of sedation.
• Using as short a scan time as possible helps minimize artifacts when scanning regions prone to movement.
• Respiratory motion can be minimized if patients are able to hold their breath for the duration of the scan.
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Patient Motion
• The sensitivity of the image to motion artifacts depends on the orientation of the motion. Therefore, it is preferable if the start and end position of the tube is aligned with the primary direction of motion, for example, vertically above or below a patient undergoing a chest scan.
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Built-in Features for Minimizing Motion Artifacts
Manufacturers minimize motion artifacts by using:
• Overscan and underscan modes• Software correction• Cardiac gating
313
Overscan and underscan modes
• The maximum discrepancy in detector readings occurs between views obtained toward the beginning and end of a 360° scan. Some scanner models use overscan mode for axial body scans, whereby an extra 10% or so is added to the standard 360° rotation. The repeated projections are averaged, which helps reduce the severity of motion artifacts. The use of partial scan mode can also reduce motion artifacts, but this may be at the expense of poorer resolution.
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Software correction
• Most scanners, when used in body scan mode, automatically apply reduced weighting to the beginning and end views to suppress their contribution to the final image. However, this may lead to more noise in the vertical direction of the resultant image, depending on the shape of the patient. Additional, specialized motion correction is available on some scanners.
315
Software correction
316
CT images of the body created with conventional reconstruction (a) and with motion artifact correction (b).
Cardiac gating• The rapid motion of the heart can lead to
severe artifacts in images. To overcome these difficulties, techniques have been developed to produce images by using data from just a fraction of the cardiac cycle, when there is least cardiac motion. This is achieved by combining electrocardiographic gating techniques with specialized methods of image reconstruction.
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Incomplete Projections
• If any portion of the patient lies outside the scan field of view, the computer will have incomplete information relating to this portion and streaking or shading artifacts are likely to be generated.
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Incomplete Projections
319
CT image of the body obtained with the patient’s arms down but outside the scanning field shows streaking artifacts.
avoid artifacts due to incomplete projections
• It is essential to position the patient so that no parts lie outside the scan field. Scanners designed specifically for radiation therapy planning have wider bores and larger scan fields of view than standard scanners and permit greater versatility in patient positioning. They also allow scanning of exceptionally large patients who would not fit within the field of view of standard scanners.
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3. Scanner-based artifacts
result from imperfections in scanner function.
a. Ring Artifacts
321
Ring Artifacts
• If one of the detectors is out of calibration on a third-generation scanner, the detector will give a consistently erroneous reading at each angular position, resulting in a circular artifact
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Ring Artifacts• Causes
1 or more bad detectorssmall offset or gain
difference of 1 detector compared to neighbors•detector calibration required
• Reason: Rays measured by a given detector are all tangent to same circle
Ring Artifacts
• A scanner with solid-state detectors is in principle more susceptible to ring artifacts than a scanner with gas detectors.
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Avoidance and Software Corrections
• recalibration the detector gain• repair services of detectors• software that characterizes and corrects
detector variations
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4. Helical and multi section technique artifacts
• In general, the same artifacts are seen in helical scanning as in sequential scanning. However, there are additional artifacts that can occur in helical scanning due to the helical interpolation and reconstruction process. The artifacts occur when anatomic structures change rapidly in the z direction (eg, at the top of the skull) and are worse for higher pitches.
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4. Helical and multi section technique artifacts
are produced by the image reconstruction process.
a. Helical Artifacts in the Axial Plane: Single-Section Scanning
b. Helical Artifacts in Multisection Scanningc. Cone Beam Effectd. Multiplanar and Three dimensional
Reformation327
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New Stuff
CT Angiography CT fluoroscopy CT virtual endoscopy / colonoscopy
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CT Angiography
This thoracic, abdominal, pelvic and lower-extremity CTA, was acquired in one acquisition of just 58 seconds using 0.5 second rotation time (8 slices/sec) and 2.5 millimeter thin slices for the entire scan.
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Fluoroscopic CT
CT virtual endoscopy / colonoscopy
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The end
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