CT is one of the frequently used diagnostic imaging modalities in Radiology. Knowledge about image quality and artifacts is essential when diagnosing a patient with the help of CT images. Moreover, Radiology Technologist's should be very well aware about the ways to identify and eliminate or minimize the artifacts in CT for better image quality.
3. Introduction
Image quality relates to how well the image represents the object scanned. However, the true test
of the quality of a specific image is whether it serves the purpose for which it was acquired.
Fundamentally, image quality in CT, as in all medical imaging, depends on 5 basic factors:
Contrast resolution,
Spatial resolution,
Temporal resolution
Image noise, and
Artifacts
Depending on the diagnostic task, these factors interact to determine the ability to perceive low-
contrast structures and the visibility of details.
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4. Image Quality
At the most fundamental level, image quality is a comparison of the image to the actual
object.
In CT, image quality is directly related to its usefulness in providing an accurate diagnosis
For example, an image of an infant using a very low technique may appear quite noisy, but it
may still be adequate if the image is taken to follow up a large abnormality, such as an
abscess.
Clearly, the usefulness of an image can only be assessed on a case-by-case basis.
Optimized imaging protocols demands that image quality should be sufficient to meet the
clinical requirement for the examination.
In many regards “quality” is a subjective notion and is dependent on the purpose for which the
image was acquired, however, here we deal primarily with objective measures of image
quality.
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5. Image Quality
A number of methods are available for measuring CT image quality, and principal characteristics
are numerically assigned. These include
spatial resolution
contrast resolution
Noise
linearity, and
uniformity.
These tools help make possible comparisons of one imaging system to another, or the same
system over time. Analytic methods attempt to assess the degree to which a system reliably
detects and accurately depicts subtle abnormalities. However, it is important to keep in mind
that the true test of the quality of a specific image is whether it serves the purpose for which it
was acquired.
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6. Spatial Resolution
It is another term used for detail resolution. It is the
system’s ability to resolve, as separate forms, small objects
that are very close together.
It is measured in line pairs per millimeter or centimeter
(lp/cm), i.e. spatial frequency
7. Spatial Resolution
Spatial Frequency
The no. of line pairs per unit length is called
spatial frequency.
Low spatial frequency represents large
objects.
High spatial frequency represents small
objects.
A simplified illustration of spatial frequency. A. If
objects are large, not many will fit in a given
length and they are said to have low spatial
frequency. B. If the objects are smaller, many
more will fit into the same length. These are said
to have high spatial frequency
9. Spatial Resolution
Spatial resolution is influenced by factors including
System geometric resolution limits – focal spot size, detector width and
ray sampling,
Pixel size
Properties of the convolution kernel/mathematical reconstruction filter
Often measured in two orthogonal directions:
Axial/In-plane (X-Y Plane) Resolution:-Determined by image matrix size,
DFOV and pixel size.
Longitudinal/Cross-plane (Z–axis) resolution:-Determined by detector
array thickness(MDCT)/collimation(SDCT).
X
Y
Z
10. Spatial Resolution
Spatial resolution of an image is measured in two ways:
Direct method (by counting the line pair):
To measure spatial resolution directly, a line pairs phantom is used
phantom is scanned, and the number of strips that are visible are counted
if 20 lines can be seen in a 1-cm section in an image of the phantom, the spatial resolution is
reported as 20 line pairs per centimeter (lp/cm).
By averaging spread of information within the system ( known as MTF)
11. Spatial Resolution
Positioning and alignment, CT number accuracy and slice thickness
Low contrast resolution
CT number uniformity assessment
High contrast (spatial) resolution
CT ACR 464 Phantom
14. Spatial Resolution
Modulation Transfer Function
Description of the ability of an imaging system to render objects of different sizes onto an image.
Describes about resolution capacity of an imaging system.
MTF is the plot of the ratio of image to object contrast (image fidelity) at each spatial frequency,
i.e. the ratio of the accuracy of the image compared with the actual object scanned.
The ideal imaging system is one that produces an image that appears exactly as the object. Such a
system would have an MTF equal to 1.
MTF is always less than 1.
Limiting resolution is the spatial frequency possible on a given CT system at an MTF equal to 0.1
In graphic form, MTF (y-axis) is charted against the spatial frequency (object size(x-axis)).
15. Spatial Resolution
By graphing the MTF of two separate CT systems, we
can compare their ability to accurately resolve objects
in the image. An MTF curve extending to the right
indicates a system with higher spatial resolution
capabilities.
The limiting resolution is the spatial frequency
possible on a given CT system, at an MTF equal to
0.1. In this example, the limiting resolution of
scanner A is 4.3 and scanner B is 5.0.
Modulation Transfer Function
17. Modulation Transfer Function
Compared with conventional radiography, CT has significantly worse spatial resolution. The
limiting spatial frequency for screen-film radiography is about 7 line pairs per millimeter
(lp/mm), for digital radiography it is about 5 lp/mm; however, the limiting resolution for CT is
approximately 1 lp/mm.
It is contrast resolution that distinguishes CT from other clinical modalities.
19. Focal Spot Size
The focal spot size affects image quality, but the effect is minimal.
As in any x-ray imaging procedure, larger focal spots cause more geometric unsharpness in the
image and reduce spatial resolution.
Although focal-spot size does affect CT spatial resolution, CT resolution is generally limited by
the size of the detector measurements (referred to as the aperture size) and by the spacing of
detector measurements used to reconstruct the image
20. Sampling (Detector width and Detector Spacing)
Applied to CT image reconstruction, sampling theorem can be roughly summarized by the
following statement: because an object may not lie entirely within a pixel, the pixel
dimension should be half the size of the object to increase the likelihood of that object being
resolved.
Nyquist criteria states that resolving N lp/cm requires measurement of at least 2 × N samples
per cm.
Spatial resolution improves significantly in longitudinal direction as the detector aperture
size decreases.
In plane (x-y) spatial resolution is not affected.
21. Sampling
In addition to small aperture closely spaced
measurements are required for good resolution.
For fixed FOV, as detector pitch decreases, number
of rays increases and give better resolution.
When the view data exhibits a sequence of higher
and lower attenuations, the image also exhibit bars
and spaces that are separate but fewer than those
actually in the test object. Such an image is said to
be aliased.
Because of insufficient sampling, the higher spatial-
frequency test pattern appears in the alias of a
lower-frequency pattern and thus is not truly
resolved.
22. Slice thickness
In single slice CT, slice thickness equal to beam collimation
In MDCT, equal to width of the detector in slice thickness direction.
Thinner Slices:
Higher Spatial Resolution
Less Partial Volume effects
More Noise
23. Image or Slice thickness
The MTF shows higher spatial resolution
along z for thinner slice images, and the
z-axis resolution degrades (the MTF
amplitude is reduced) as the
reconstructed slice thickness increases.
24. Slice Sensitivity Profile
Is a graph that shows the effect of broadening of slice in z-axis.
SSP is rectangular and width is equal to section width , but in spiral scan they are extended and
more peaked.
Due to continuous movement of patient through gantry the data are displaced along z axis
causing widening of slice sensitivity profile.
FWHM of SSP gives Effective slice thickness.
25. Slice Sensitivity Profile
Increase in pitch widens SSP
Increase in pitch means movement is greater than the collimation , so there is increased slice
distortion and increase in effective slice thickness.
360˚ linear interpolation algorithm also widens slice sensitivity profile (replaced by 180˚ linear
interpolation algorithm)
SSP in 180˚ linear interpolation is reduced so allowed imaging at pitch greater than 1.
26. Slice Sensitivity Profile
Thickness of the slice that is actually
represented on the CT image, as opposed to the
size selected by the collimator opening. In
traditional axial scanning, selected slice
thickness is equal to effective slice thickness.
However, because of the interpolation process
used in helical scanning, the effective slice
thickness may be wider than the selected slice
thickness. Also called the effective slice
thickness.
27. Slice Sensitivity Profile
illustrates that in one multi-detector scanner,
the table speed can affect the slice
sensitivity profile and effective slice
thickness. The top curve was obtained
using 4 x 5mm collimation mode, pitch of
0.75 (table speed of 15 mm/rot) and a
nominal reconstructed slice thickness of
5mm; the calculated FWHM was 5.31 mm.
The bottom curve was obtained using the
same parameters except that the pitch was
increased to 1.5 (30 mm/rot) and the
resulting calculated FWHM was 6.24 mm; a
17% increase.
28. Tradeoff Between Spatial Resolution and
Slice thickness
At same KV and mAs, number of detected photons varies linearly with slice thickness.
Thinner slice provides higher spatial resolution but increased image noise.
Thicker Slice provides higher contrast resolution but poor spatial resolution.
29. Pixel Size,FOV and matrix Size
Smaller the pixel size better is the spatial resolution
Transverse (in plane xy) resolution depends on pixel size
Pixel size = DFOV/Matrix size.
DFOV defined by the user based on anatomy to be
displayed-DFOV<SFOV.
Two small objects in the patient. B. When reconstructed to
lie within a single pixel, they will be represented on the
image as a single object. C. If a smaller pixel is used, the
objects can be displayed as two distinct shapes.
30. Reconstruction Filter
Mathematical filter applied during reconstruction (filtered back projection) to remove the blur from
images.
Affects spatial resolution but requires tradeoffs depending on clinical needs.
Sharp- high spatial resolution but yields greater image noise.
Soft or Smooth- Reduces image noise but also degrades spatial resolution.
31. Reconstruction Filter
FIGURE 8. CT spatial resolution phantom, consisting of 4–12 line-pairs per centimeter (from American College
of Radiology accreditation phantom), reconstructed using standard (A) and bone (B, high-resolution) filters.
32. Contd…
shows the MTF of two different reconstruction
filters measured on a multidetector scanner (GE
LightSpeed Qx/I). This figure shows that the
“Bone” algorithm maintains a higher amplitude
modulation than the “Standard” algorithm.
33. Isotropic Spatial Resolution
It is the resolution where the cross-plane resolution (z) match that of the in-plane (x-y)
Since in most CT scans the pixel length is considerably smaller than the slice thickness, the
reformatted scan can have an unusual appearance or stair-step artifact
Modern MDCT for body imaging has isotropic resolution.
Advantages :-
Creates MPR images with the same spatial resolution as the original sections.
Avoids the need for direct coronal scanning; reducing dose and acquisition time
35. Contrast Resolution
Ability of a system to differentiate objects with similar densities on the image.
CT is far superior in detecting low contrast differences
Radiography can discriminate a density difference of approximately 10%, CT can detect density
differences from 0.25% to 0.5%, depending on the scanner
36. Contrast Resolution
Low-contrast resolution can be measured with phantoms that contain low-contrast objects of
different sizes.
1% contrast difference corresponds to a difference of 10 HU
The ability to image low-contrast objects with CT is limited by the size and uniformity of the object
and by the noise of the system.
Because the difference between object and background is small, noise plays an important role in
low-contrast resolution.
37. Contrast Resolution
No large differences are noted in mass density and
effective atomic number among tissues, but the
differences are greatly amplified by computed tomography
imaging.
38. Factors affecting Contrast Resolution
Pixel Size:- If all parameters are fixed ,increase in FOV increases pixel dimension and the no of x-
rays passing through the pixel thereby increasing CR.
mAs :- By decreasing the mAs(tube current) increases the image noise and decreases the contrast
resolution.
Slice Thickness :-
Increasing the Slice thickness leads to improved contrast resolution at the expense of Spatial
resolution.
Decreasing the Slice thickness leads to decreased SNR and therefore degrades Contrast
Resolution(other factors constant)
39. Factors affecting Contrast Resolution
Reconstruction Filter:- Bone filter produce lower contrast resolution and soft tissue filter improves
contrast resolution
Patient Size :- For same x-ray technique, larger patient attenuate more photons resulting in
detection of fewer photons causes reduction in SNR as well as contrast resolution
Gantry Rotation Speed :- Faster the gantry rotation speed lesser the contrast resolution.
40. Factors affecting Contrast Resolution
The effect of window settings on low-contrast resolution. A hypo attenuating mass is seen in the medial
segment of the left hepatic lobe (arrow). The liver lesion is more easily discernible when the image is
displayed with a narrow window width (A). The same image, displayed with a wider window width—the
liver lesion is nearly indistinguishable (B).
41. Noise
It is the local statistical fluctuation in the CT numbers of
individual picture elements of a homogeneous ROI.
Even if we image a perfectly uniform object (e.g. a water
filled object) there is still a variation in the Hounsfield units
about a mean. This is due to noise.
Noise degrades the image by degrading low contrast
resolution and introducing uncertainty in the Hounsfield
units of the images.
CT no. are the average values i.e. pixels have a range of
values greater than or less than CT no., these variation of
pixel value represents image noise.
42. Noise
The major types of noise include quantum mottle, electronic mottle and computational mottle.
The dominant source of image mottle:- Quantum mottle.
Characterized by a grainy appearance of the image.
Reducing the mAs is expected to increase the noise (measured standard deviation) by 1/√mas.
Therefore, if the mAs is reduced by ½, then noise should increase by √2 =1.414 à(40% increase)
43. Noise
radiation dose levels varying by about a factor of 4 (285 mAs/71 mAs < 4.0). The circles visible in the phantom correspond to
0.6% differences in contrast (6 HU), and different rows of the circles have different diameters, which result in different signal-to-
noise ratios (SNRs) of the circles. It is clear that more of the circular test objects are visible in the higher dose image on the left.
The standard deviation, s, is measured using software on most CT scanners or PACS systems. The standard deviation is seen to
vary by a factor of two, for these images that used a fourfold difference in radiation dose, illustrating the Poisson relationship that
image noise is relative to the square root of the dose.
44. Noise
Depends on number of photons used by the detector to form an image which
depends on several factors:-
Incident x ray intensity (kVp , mAs and filtration)
Quantum detection efficiency of detector
Slice thickness
Reconstruction filter or kernel.
45. 8/11/2021 45
Temporal resolution
Temporal resolution is the ability to resolve fast moving objects in the displayed CT image.
Good temporal resolution avoids motion artifacts and motion induced blurring of the image.
A good temporal resolution in CT is realized by fast data acquisition (fast rotation of the X-ray tube)
Temporal resolution can be improved further by using dedicated reconstruction algorithms (cardiac
CT with a segmented reconstruction) or by using a dual source CT scanner.
46. Factors Affecting Temporal Resolution
Gantry rotation time- decrease in gantry rotation time increases temporal resolution
Number of detector channel- increase in detector channel in z-direction increases temporal
resolution
Reconstruction method- single-segment reconstruction method has less temporal resolution than
multi-segment reconstruction method
47. Linearity
This refers to the relationship between CT numbers and the linear
attenuation values of the scanned object at a designated kVp value.
CT no. should be consistently same for a particular tissue. Eg.- For
water= 0
To check linearity, calibration should be done frequently by catphan
or 5 pin performance test phantom
Each of the 5 pins are made up of diff. plastic material having known
physical and x-ray attenuation properties
Plot of CT No. Vs linear attenuation co-efficient should be straight
line.
Deviations from linearity should not exceed +/- 5HU over specific ranges
(soft tissue or bone).
Linearity is typically measured semiannually
48. Linearity
Computed tomography (CT) linearity is acceptable if a
graph of average CT number versus the linear
attenuation coefficient is a straight line that passes
through 0 for water.
49. Uniformity
The CT No. measurement should not change with the location of the
selected region of interest (ROI) or with the phantom position
relative to the isocentre of the scanner.
This characteristic of CT system is known as spatial uniformity.
uniformity is most commonly measured using a water phantom.
For uniformity measurements, there should be no more than a ±2
HU variation from an ROI placed at the center of the water
phantom to those placed at the periphery.
These tests should be performed on a weekly basis
50. Artifacts In CT
Definition of an image artifact is not as clearly defined as one might expect.
Artifact is “an unwanted density in an image which may not be present in the object”
In computed tomography (CT), the term artifact is applied to any systematic discrepancy
between the CT numbers in the reconstructed image and the true attenuation coefficients
of the object.
51. Classification of Artifacts
On the basis of Appearance:
Appearance Cause
Streaks -Improper sampling data, partial volume average, Pt motion, Beam
hardening, Noise, spiral/ helical, Mechanical failure
Shading -Partial volume averaging , Beam hardening, Spiral/ Helical, Scatter
radiation, Off focal radiation , Improper projection
Rings/Bands -Bad detector channel
52. Classification of Artifacts
On the basis of Appearance:
Different appearances of artifacts. A, Streak. B, Ring. C, shading.
53. Classification of Artifacts
On the basis of Origin
Physics based-
Beam Hardening
Partial volume effect
Photon starvation
Under sampling
Edge gradient artifact
Patient based-
Metal artifacts
Motion artifacts
Out of field
Scanner based
Ring Artifact
Tube Arcing
Helical and Multisection-
Cone beam artifacts
Wind mill Artifacts
Artifacts due to Multiplanar and 3-D reformation
Stair step Artifacts
Zebra artifacts
54. Classification of Artifacts
Physics Based Artifacts
Beam hardening artifacts.
Partial volume artifacts.
Photon starvation.
Under sampling
Edge gradient artifact
Patient based artifacts
Scanner based artifacts
Helical & multi-section artifacts.
55. Beam Hardening Artifacts
Refers to an increase in the mean energy of the x-ray beam as it passes through the patient
Caused by polychromatic nature of the beam.
Low energy photons are preferentially absorbed, beam becomes more penetrating causing
underestimation of the attenuation coefficient(HU).
The beam hardening phenomenon induces artifacts in Ct because rays from some projection angles
are hardened to a differing extent than rays from other angles and this confuse the reconstruction
algorithm.
56. Beam Hardening Artifacts
Effect of beam hardening as the x-ray beam traverses
different object sizes. A, Original spectrum. B, After
traversing 15 cm water. C, After traversing 30 cm water.
57. Beam Hardening Artifacts
A . Cupping artifacts :
Occurs when hardening is more prone in the center and less at the periphery. It resembles a
cup.
the resultant attenuation profile differs from the ideal profile that would be obtained
without beam hardening. A profile of the CT numbers across the phantom displays a
characteristic cupped shape
B . Streaks and dark band
In very heterogeneous cross sections, dark bands or streaks can appear between two dense
objects in an image.
If a high density materials severely reduces transmission, the detector may record no
transmission and streaks and dark band appear.
58. Beam Hardening Correction
Filtration :- a flat piece of metallic material is used to pre-harden the beam and also a bow tie
filter is used
Calibration correction :- Scanners are calibrated using phantoms in a range of sizes
Beam hardening correction software :-Iterative correction algorithm may be applied when
images of bony regions are being reconstructed
By Operator :- avoid scanning bony regions, either by means of patient positioning or 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.
Using dual energy CT technique
59. Beam Hardening Artifacts
CT number profiles obtained across the center of a
uniform water phantom without calibration correction
(a) and with calibration correction (b)
Attenuation profiles obtained with and without beam
hardening for an x-ray beam passing through a uniform
cylindrical phantom.
60. Beam Hardening Artifacts
CT image shows streaking artifacts due to the beam
hardening effects of contrast medium.
Beam hardening from the dense petrous
bones creates low attenuation streaks in
the image (arrows)
62. Beam Hardening Correction
dark banding
CT images of the posterior fossa show the
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
63. Partial Volume Artifacts
Result of averaging the linear attenuation coefficient in a voxel that is heterogeneous in composition .
Arise when voxel contain many types of tissues.
Arise essentially from reconstructing low resolution images, typically thick slice images.
It produces CT numbers as an average of all types of tissues.
It will appear as bands or streaks.
These artifacts are a separate problem from partial volume averaging, which yields a CT number
representative of the average attenuation of the materials within a voxel.
64. Partial Volume Artifacts
(7) Mechanism of partial volume artifacts, which occur when a dense object lying off-center
protrudes part of the way into the x-ray beam. (8) CT images of three 12-mm-diameter
acrylic rods supported in air parallel to and approximately 15 cm from the scanner axis. (a)
Image obtained with the rods partially introduced into the section width shows partial
volume artifacts. (b) Image obtained with the rods fully introduced into the section width
shows no partial volume artifacts.
66. Partial Volume Artifacts
Remedy
Partial volume artifacts can best be avoided by using a thin acquisition section width. This is
necessary when imaging any part of the body where the anatomy is changing rapidly in the z
direction, for example in the posterior fossa. To limit image noise, thicker sections can be generated
by adding together several thin sections.
Another method for reducing the impact of partial volume artifacts is to reconstruct multiple CT
projections, such as the axial and coronal projections. What appears as a partial volume artifact in
one projection can usually be ruled out by visualizing the same region in the other projection
While partial volume artifacts can still occur, the dramatic reduction in the volume of a voxel in the
past decade has substantially reduced the role that partial volume artifacts play in the diagnosis in
modern CT examinations.
67. Partial Volume Artifacts
A. A 5-mm thick CT image through the lungs are shown, and a very small lesion is seen (circle) that has lower HU values
consistent with lung cancer. B. When the same lesion is seen with thin section (1.25 mm) reconstruction, the contrast of the
lesion is not diluted due to partial volume averaging, and the high HU values are evident, consistent with a benign diagnosis.
68. Photon Starvation Artifacts
Occurs in highly attenuating region due to inefficient photons passing through the widest part of the
patient.
Manifestation of irregularities caused by noise in the raw data profile
Image appears noisy with streaks
69. Photon Starvation Artifacts
Remedy
Automatic Tube Current Modulation: the tube current is automatically varied during the course of each
rotation
Adaptive Filtration: This software correction smooths the attenuation profile in areas of high attenuation
before the image is reconstructed
71. Photon Starvation Artifacts
Projection data as they might appear for a horizontal
x-ray beam passing through the shoulders. Diagrams
show the data in their original form (a) and with
adaptive filtration (b).
Original axial CT images (top) and coronal
reformatted images (bottom) in their
original form (a) and after reconstruction
with multidimensional adaptive filtration
(b).
72. Undersampling/Aliasing
Too large an interval between projections (under sampling) can
result in misregistration relating to sharp edges and small
objects. This leads to an effect known as view aliasing, where
fine stripes appear to be radiating from the edge of, but at a
distance from, a dense structure
Stripes appearing close to the structure are more likely to be
caused by undersampling within a projection, which is known as
ray aliasing.
may not have too serious an effect on the diagnostic quality of an
image
However, where resolution of fine detail is important,
undersampling artifacts need to be avoided as far as possible
CT image of a Teflon block in a
water phantom shows aliasing
(arrow) due to undersampling of
the edge of the block
73. Undersampling/Aliasing
Reduction method
View aliasing: Increasing the largest possible no. of projection per rotation
Ray aliasing: Using high resolution technique like flying focal spot and quarter
detector shift
74. Edge Gradient Artifact
Arise from irregularly shaped object that have a
pronounced difference in density from surrounding
structure
A common clinical example is artifacts that result when
barium and air lie adjacent to each other in the stomach
Results in streak artifact or shading
Remedy
Using thinner slices
Using a low HU- value oral contrast
Change in patient’s position
The irregular shading in the left lobe of the
liver (indicated by arrows) in this image is
caused by a combination of edge gradient
effect and beam hardening. The artifacts
arise from the pronounced difference in
density between the air and barium in the
stomach
75. Classification of Artifacts
Physics based artifacts
Patient based artifacts
Metal artefacts
Motion artefacts
Incomplete projections
Scanner based artifacts
Helical & multisection artifacts
76. Metal Artifacts
Manifest itself as “star streaking” artifact.
It’s caused by presence of metallic objects inside or
outside the patient.
Metallic object absorbs the photons causing an incomplete
attenuation profile.
Reduction methods:-
A. By operator :-
Taking off removable metal objects before scanning
Use of gantry angulation
Increase technique (kv)
Use thin slices
77. Metal Artifacts
B. By software correction :-
Artifact reduction (MAR) algorithms are used to improve CT image quality in patients with metal
ware
There are a number of commercially-available algorithms (in 2019):
Iterative MAR (iMAR) - Siemens
MAR for orthopedic implants (O-MAR) - Philips
single-energy MAR (SEMAR) - Toshiba/Canon
SmartMAR – GE
Beam hardening correction software should also be used when scanning metal objects to minimize
the additional artifacts due to beam hardening.
The usefulness of metal artifact reduction software is sometimes limited because, although
streaking distant from the metal implants is removed, there still remains a loss of detail around
the metal-tissue interface
78.
79. Metal Artifacts
CT images of a patient with metal spine implants, reconstructed without any
correction (a) and with metal artifact reduction (b
81. Motion Artifacts
Occurs due voluntary/involuntary motions, sometimes
random or unpredictable motions.
Produces “GHOSTING” Effect.
Image appears– as if it is composed of superimposed
images.
The diagonal shading degrading
this image is caused from patient
movement during the scan
82. Motion Artifacts
Remedy
By operator
Positioning aids - prevent voluntary movement in most patients.
Sedation - to immobilize the patient (eg,pediatric patients)
Short scan time
Breath hold
Built-in Features for Minimizing Motion Artifacts
Overscan and underscan modes: 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% 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.
Software correction
Cardiac gating for cardiac imaging
84. Out of field/Incomplete Projection
Artifacts
Occurs when patient dimension exceed scan field.
If any portion of the Pt. lies outside the scan field of
view, the computer will have incomplete
information relating this portion and streaking or
shading artifacts can result.
Reduction:-
Selection of larger SFOV unit if possible.
Proper positioning; e:g. Raising patients arms above
their head on the scan of chest and abdomen
85. Classification of Artifacts
Physics based artifacts
Patient based artifacts
Scanner based artifacts
Ring artifacts
Tube arcing
Helical & multisection artifacts.
86. Ring Artifacts
Occurs in 3rd generation scanner, due to miscalibration of
any one of the detectors.
The detector will record incorrect data in each angular
position.
Detectors towards the center of the detector array
contributes ring artifact that is small in diameter than
detector in periphery
88. Avoidance of Ring Artefacts
Detector calibration
Detector replacement
Selecting the correct scan field of view
Software corrections
89. Tube Arcing
Occurs when there is a short circuit within the tube, typically from cathode to tube envelope.
Tungsten vapor from anode and cathode intercepts the projectile electrons intended for
collisions with the target.
Causes momentary loss of x-ray output.
Appear as near-parallel and an equidistant streak pattern on transaxial computed tomography
(CT) images and as a “horizontal” hypodense band on the coronal and sagittal CT images.
Remedy:
Tube Replacement.
90. Tube Arcing
CT tube arcing artifact seen in the head region on the
transaxial image (A) and corresponding coronal image
(B); in the thigh region on the transaxial image (C) and
corresponding coronal image (D)
Plot of generator kV versus time in
images showing drop of voltage
corresponding to appearance of tube
arcing artifact (A and B)
91. Classification of Artifacts
Physics based artifacts
Patient based artifacts
Scanner based artifacts
Helical & multi-section artifacts.
Cone beam artifacts
Wind mill
92. Helical Artifacts in the Axial Plane
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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Consecutive axial CT images from a helical scan of a
cone-shaped phantom lying along the scanner axis.
93. Helical Artifacts in the Axial Plane
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Series of CT images from a helical scan of the abdomen shows helical artifacts (arrows).
94. Helical Artifacts in the Axial Plane
To keep helical artifacts to a minimum
steps must be taken to reduce the effects of variation along the z axis
This means using, where possible, a low pitch, a 180° rather than 360° helical interpolator
thin acquisition sections rather than thick.
Sometimes, it is still preferable to use axial rather than helical imaging to avoid helical
artifact
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95. Cone Beam Effect
Caused by incomplete or insufficient projection samples as a result of the cone beam geometry of
multislice CT.
As the number of sections acquired per rotation increases, a wider collimation is required and the x-
ray beam becomes cone shaped rather than fan shaped.
96. Cone Beam Effect
Detector elements in the periphery of the array are
exposed more obliquely to those of the center.
However, it is drastically reduced by use of cone beam
reconstruction algorithms
97. Cone Beam Effect
Cone beam effect is more apparent
with larger cone angle or large
pitch
CT images from data collected by an outer detector row
(a) and an inner detector row (b) show cone beam
artifacts around a Teflon rod, which was positioned 70
mm from the isocenter at an angle of 60° to the scanner
axis.
98. Wind Mill Artifact
More complicated form of axial image distortion.
Seen in thin slice images reconstructed from high pitch
helical multislice CT images.
Type of aliasing artifact
The term wind mill comes from the spiral appearance of
shading artifact.
Remedy
Z-filter helical interpolators
Using low pitch when possible
99. Avoidance and Correction of Helical and
Cone Beam Artifacts
Reconstruction techniques like 3D Back projection, Adaptive multiple plane reconstruction
(AMPR), Weighted Hyper plane reconstruction (WHR) are used that account for the cone
beam angle thereby reducing cone beam artifact
Lower Pitch (<1) can be used
Z sampling methods used during reconstruction to remove windmill artifact.
100. Classification of artefacts
Physics based artifacts
Patient based artifacts
Scanner based artifacts
Helical & multi-section artifacts.
Artifacts due to Multiplanar and 3-D Reformation
Stair Step Artifacts
Zebra Artifacts
101. Stair Step Artifacts
Improper selection of slice thickness and slice increment when generating MPR and 3D image.
Appears around the edges of the structures in the reformatted images.
Less severe with the helical scans .
102. Stair Step Artifacts
Remedy:
Using Thin slice
50% overlap on recon slice incrementation.
Stair step artifacts are virtually eliminated in multiplanar and three-dimensional reformatted
images from thin-section data obtained with today’s multisection scanners
103. Zebra Artifacts
Appears as faint stripes in the Multiplanar and 3D reformatted
images from helical interpolation.
Because the helical interpolation process gives rise to a degree of
noise inhomogeneity along the z axis
Becomes more pronounced away from the axis of rotation because
the noise in homogeneity is worse at off-axis
Maximum intensity projection image obtained with
helical CT shows zebra artifact
106. Conclusion
There is always compromise between spatial resolution, contrast resolution and the random
noise.
Demand for resolution has been the driving force behind MDCT technology’s strive for thinner
detectors in z-direction.
Artifacts arise from a range of sources and can degrade the quality of an image to varying
degrees.
Designed features incorporated in some scanners minimizes some artifacts and some can be
partially corrected by the scanner software.
Careful patient positioning and optimum selection of scan parameters are the most important
factors in avoiding image artifacts.
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Tradeoffs in CT Image Quality and Radiation Dose ... aapm.org/meetings/04AM/pdf/14-2328-
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Reference
An underlying principle of CT, We pay for image quality with radiation dose.
Larger matrices with small pixels and high subject contrast have better spatial resolution. Utilizing small focal spots and narrow collimation provides better spatial resolution.
The absolute object size that can be resolved is equal to one-half the reciprocal of the spatial frequency at the limiting resolution.
Larger matrices with small pixels and high subject contrast have better spatial resolution. Utilizing small focal spots and narrow collimation provides better spatial resolution.
Larger matrices with small pixels and high subject contrast have better spatial resolution. Utilizing small focal spots and narrow collimation provides better spatial resolution.
Larger matrices with small pixels and high subject contrast have better spatial resolution. Utilizing small focal spots and narrow collimation provides better spatial resolution.
Larger matrices with small pixels and high subject contrast have better spatial resolution. Utilizing small focal spots and narrow collimation provides better spatial resolution.
Pitch greater than one- high speed mode , less than one- high resolution mode.
The contrast between a structure and its surroundings is ONLY detectable if it is 3-5 times greater than the noise in the image.
daptive multisegment image reconstruction [12], which uses up to four segments correlated with the raw data from up to four consecutive heartbeats, and (ii) standard halfscan reconstruction, which uses a single 180° gantry rotation.
Posterior cranial fossa is the most critical region to produce partial volume artifact.
The object fills detector stream 2 resulting in a very high attenuation (white). In detector stream 3 none of the dense object is imaged and so the attenuation is low (black). In detector stream 1 the object is only partially imaged and so the attenuation is an average between the dense object and the less dense background.
MAR, metal artifact reduction; OMAR, orthopedic metal artifact reduction; iMAR, iterative metal artifact reduction; SEMAR, single-energy metal artifact reduction; SmartMAR, Smart metal artifact reduction; AMPP, Artifact Management for Proton Planning
Scanners with solid state detectors – more prone
Small structure, such as piece of bone is detected by beam from one direction but is missed by opposing beam resulting inconsistency , leads to streak artifact
Such effect is more apparent with larger cone angle or large pitch
air calibration scans: influence of the bow tie filter is characterized, characterize differences in individual detector response
Rapid technical developments and expanding list of applications have led to a dramatic increase in the use of CT.
The clinical utility of any modality lies in its spatial and contrast resolution.