ct seeram chapter 11: image quality. ct image quality parameters spatial resolution image noise...
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CT
Seeram Chapter 11:
Image Quality
SpatialResolution
ImageNoise
ContrastResolution
Artifacts
BeamCharacteristics
DoseSlice
Thickness
Scatter
DisplayResolution
ReconstructionAlgorithm
SubjectTransmissivity
Spatial ResolutionQuantifies 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 two objects
Spatial Resolution
Resolvable Object Size &Limiting Resolution
Smallest resolvable high contrast objectOften expressed as line pairs / cm“Pair” is one object + one space
OnePair
Resolvable Object Size:Limiting ResolutionSmallest resolvable high contrast object is
half the reciprocal of spatial frequencyExample:
Limited resolution = 15 line pairs per cmPair is 1/15th cmObject is half of pair
1/15th / 2 1/30th cm .033 cm 0.33 mm
1/15th cm
1/30th cm
Geometric Factors affectingSpatial Resolution
Focal spot sizedetector aperture widthslice thickness or collimationLess variation likely for thinner slices
attenuation variations within a voxel are averagedpartial volume effect
Geometric Factors affectingSpatial Resolution
focal spot - isocenter distance
focal spot - detector distance
Finite focalspot size
Geometric Unsharpness & CTDecreased spatial resolution if object blurred over several detectors
Detector aperture sizemust be < object for object to be resolved
Focal Spot
Detectors
Small Object to be
Imaged
Non-geometric Factorsaffecting Spatial Resolution
# of projectionsDisplay matrix size
512 X 512 pixels standardReconstruction algorithms
smoothing or enhancing of edges
Reconstruction Algorithm &Spatial ResolutionBack projecting blurs imageAlgorithms may be anatomically specific
Special algorithmsedge enhancementnoise reductionsmoothingsoft tissue or bone emphasis
Hi-Resolution CT TechniqueVery small slice thicknesses
1-2 mmHigh spatial frequency algorithms
increases resolution increases noise Noise can be offset by using higher doses
Optimized window / level settingsSmall field of view (FOV)
Known as “targeting”
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
CT Contrast Resolution
Significantly better than radiographyCT can demonstrate very small differences in
density and atomic #
Radiography10%
CT<1%
This’ll be on your test. I guarantee it.
CT Contrast Resolution Depends Upon
reconstruction algorithmlow spatial frequency algorithm smooths
image Loss of spatial resolution Reduces noise
enhances perceptibility of low contrast lesions
image display
CT Contrast Resolution Depends on Noise
CT Contrast Resolution
Contrast depends on noise
Noise depends on # photons detected
# photons detected depends on …
# of Photons Detected Depends Upon
photon flux (x-ray technique)slice thicknesspatient sizeDetector efficiencyNote:
Good contrast resolution requires that detector sensitivity be capable of discriminating small differences in intensity
Small Contrast Difference Harder to Identify in Presence of Noise
CT Image NoiseFluctuation of CT
#’s in an image of uniform material (water)
Usually described as standard deviation of pixel values
CT Image Noise
Standard deviation of pixel values
(xi - xmean)2
Noise () = -------------------(n-1)
Xi = individual pixel valueXmean = average of all pixel values in ROIn =total # pixels in ROI
Noise Level
UnitsCT numbers (HU’s)
or% contrast
Noise Measurement in CT
Scan water phantomSelect regions of
interest (ROI)Take mean & standard
deviation in each regionStandard deviation
measures noise in ROI
CT Noise Levels Depend Upon
# detected photons quantum noise
matrix size (pixel size) slice thickness algorithm electronic noise scattered radiation object size Photon flux to
detectors…
Photon Flux to Detectors
Tube output flux (intensity) depends uponkVpmAsbeam filtration
Flux is combination of beam quality & quantity
Flux to detectors modified by patientLarger patient = less photons to detector
Slice ThicknessThinner 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
Noise Levels in CT:Increasing slice width = less noise
BUTIncreasing slice width degrades spatial
resolutionless uniformity inside a larger pixelpartial volume effectpartial volume effect
2() = kT/(td3R)
Where is variance resulting from noisek is a conversion factor (constant)T is transmissivity (inverse of attenuation)t is slice thicknessd is pixel sizeR is dose
Noise Levels in CT:When dose increases, noise decreases
dose increases # detected photonsDoubling spatial resolution (2X lp/mm)
requires an 8X increase in dose for equivalent noiseSmaller voxels mean less radiation per
voxel
2() = kT/(td3R)
If slice thickness goes down by 2 Dose must go up by 2
To hold noise constant
Measurements of Image Quality
PSF = Point Spread FunctionLSF = Line Spread FunctionCTF = Contrast Transfer FunctionMTF = Modulation Traffic Function
Point Spread FunctionPSF
“Point” object imaged as circle due to blurring
Causesfinite focal spot sizefinite detector sizefinite matrix sizeFinite separation between object and
detector Ideally zero
Finite distance to focal spot Ideally infinite
Quantifying BlurringObject point becomes image circleDifficult to quantify total image circle size
difficult to identify beginning & end of object
Intensity
?
Quantifying BlurringFull Width at Half Maximum (FWHM)width of point spread
function at half its maximum value
Maximum value easy to identify
Half maximum value easy to identify
Easy to quantify width at half maximum
FWHM
Maximum
HalfMaximum
Line Spread FunctionLSF
Line object image blurredImage width larger than object width
Intensity
?
Contrast Response FunctionCTF or CRF
Measures contrast response of imaging system as function of spatial frequency
LowerFrequency
HigherFrequency
Loss of contrast between light and dark areas as bars & spaces get narrower. Bars & spaces blur into one another.
Contrast Response FunctionCTF or CRFBlurring causes loss of contrast
darks get lighterlights get darker
LowerFrequency
HigherFrequency
HigherContrast
LowerContrast
CT PhantomsAvailable from
CT manufacturerprivate phantom
manufacturersAmerican Association
of Physicists in Medicine AAPM
Measure• noise
spatial resolution• contrast resolution• slice thickness• dose
CT Spatial vs. Contrast ResolutionSpatial & contrast resolution interact
High contrast objects are easier to resolveOmprove one at the expense of the otherCan only improve both by increasing dose
Increasing object size
Increasing contrast
Contrast & DetailLarger objects easy to see even at low
contrast
Increasing object size
Increasing contrast
Contrast & DetailSmall objects only visible at high contrast
Increasing object size
Increasing contrast
Contrast – Detail RelationshipContrast vs. object diameter
less contrast means object must be larger to resolve
Difference in CT #
Object Diameter
Increasing object size
Increasing contrast
Visibility
Modulation Transfer FunctionMTF
Fraction of contrast reproduced as a function of frequency
RecordedContrast
(reduced by blur)frequency
MTF
1
0Contrast provided
to film
Freq. =line pairs / cm
50%
MTF
Can be derived frompoint spread functionline spread function
MTF = 1 meansall contrast reproduced at this frequency
MTF = 0 meansno contrast reproduced at this frequency
MTF
If MTF = 1all contrast reproduced at this frequency
RecordedContrast
Contrast providedto film
MTF
If MTF = 0.5half of contrast reproduced at this
frequency
RecordedContrast
Contrast providedto film
MTF
If MTF = 0no contrast reproduced at this frequency
RecordedContrast
Contrast providedto film
CT Number
Calculated from reconstructed pixel attenuation coefficient
t - W)CT # = 1000 X ------------
W
Where:ut = linear attenuation coefficient for tissue in pixeluW = linear attenuation coefficient for water
LinearityLinear relationship of CT #’s to
object linear attenuation coefficientsChecked with phantom of several
known materialsaverage CT # of each material
obtained from ROI analysisCompare CT #’s with known
coefficients
325
-100
50 -44
77
Cross-Field Uniformity Use uniform phantom (water) CT pixel values should be uniform
anyplace in image Take 5 ROI
1 center ROI4 corners ROI’s
Compare standard deviation between ROI’s
CT ArtifactsDistortionAreas where image
not faithful to subjectSources
patientimage processequipment
CT ArtifactsDistortion
Phantoms with evenly distributed objects
Preview!CT Artifacts: Causesmotionmetal & high-contrast
sharp edgesbeam hardeningpartial volume averagingsamplingdetectors
Motion Artifacts
Causes streaks in imageAlgorithms have trouble coping because of
inconsistent data
Artifacts: Abrupt High Contrast Changes Examples:
prostheses dental fillings surgical clips Electrodes bone
Metal absorbs all radiation in ray causes star-shaped artifact
Can be reduced by software
CT Artifacts:Beam Hardening
Increase in mean energy of polychromatic beam as it passes through patient
Can cause broad dark bands or streakscupping artifact
Reduced by beam hardening correction algorithms
CT Artifacts:Partial Volume EffectCT #’s based on linear attenuation coefficient for
tissue voxelsIf voxel non-uniform (contains several materials),
detection process will average
Partial Volume Effect
Can appear as incorrect densities streaks bands
Minimizing Use thinner slices
Image Artifacts:Ring Artifact in 3rd GenerationCauses
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
Quality Control in CTPerformance tested at prescribed intervals
• spatial resolution
• contrast resolution
• noise
• slice width
Image Quality Tests
• kVp waveform
• average & standard deviation of water phantom CT #
• scatter & leakage