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Artifacts in CT: Recognition and Avoidance¹

¹ From Imaging Performance Assessment of CT Scanners (ImPACT), St George’s Hospital, Blackshaw Rd, London SW17 0QT, England. Presented as an education exhibit at the 2003 RSNA scientific assembly. Received April 5, 2004; revision requested May 7; final revision received August 20; accepted September 1. Both authors have no financial relationships to disclose. Address correspondence to J.F.B. (e-mail: julia@beamed.wanadoo.co.uk).

View larger version (22K): [in a new window]   Figure 1.  Changing energy spectrum of an x-ray beam as it passes through water. The mean energy increases with depth. (The attenuated spectra have been rescaled to be equivalent in size to the unattenuated spectra.)

View larger version (25K): [in a new window]   Figure 2.  Attenuation profiles obtained with and without beam hardening for an x-ray beam passing through a uniform cylindrical phantom.

View larger version (124K): [in a new window]   Figure 3a.  CT number profiles obtained across the center of a uniform water phantom without calibration correction (a) and with calibration correction (b).

View larger version (124K): [in a new window]   Figure 3b.  CT number profiles obtained across the center of a uniform water phantom without calibration correction (a) and with calibration correction (b).

View larger version (83K): [in a new window]   Figure 4.  CT image shows streaking artifacts due to the beam hardening effects of contrast medium.

View larger version (103K): [in a new window]   Figure 5a.  CT images of a skull phantom reconstructed without bone correction (a) and with bone correction (b).

View larger version (118K): [in a new window]   Figure 5b.  CT images of a skull phantom reconstructed without bone correction (a) and with bone correction (b).

View larger version (101K): [in a new window]   Figure 6a.  CT images of the posterior fossa show the 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). (Reprinted, with permission, from reference 1.)

View larger version (97K): [in a new window]   Figure 6b.  CT images of the posterior fossa show the 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). (Reprinted, with permission, from reference 1.)

View larger version (29K): [in a new window]   Figure 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.

View larger version (79K): [in a new window]   Figure 8a.  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 intruded into the section width shows partial volume artifacts. (b) Image obtained with the rods fully intruded into the section width shows no partial volume artifacts.

View larger version (65K): [in a new window]   Figure 8b.  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 intruded into the section width shows partial volume artifacts. (b) Image obtained with the rods fully intruded into the section width shows no partial volume artifacts.

View larger version (59K): [in a new window]   Figure 9.  CT image of a shoulder phantom shows streaking artifacts caused by photon starvation.

View larger version (17K): [in a new window]   Figure 10.  Tube current modulation as a function of tube angle. mA = milliamperage.

View larger version (18K): [in a new window]   Figure 11a.  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).

View larger version (21K): [in a new window]   Figure 11b.  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).

View larger version (16K): [in a new window]   Figure 12a.  The three components of multidimensional adaptive filtration: averaging of adjacent in-plane detector readings (a), averaging of each detector reading at successive projection angles (b), and broadening of the z filter for high-attenuation angles (c). Black line in c = reconstruction position.

View larger version (23K): [in a new window]   Figure 12b.  The three components of multidimensional adaptive filtration: averaging of adjacent in-plane detector readings (a), averaging of each detector reading at successive projection angles (b), and broadening of the z filter for high-attenuation angles (c). Black line in c = reconstruction position.

View larger version (46K): [in a new window]   Figure 12c.  The three components of multidimensional adaptive filtration: averaging of adjacent in-plane detector readings (a), averaging of each detector reading at successive projection angles (b), and broadening of the z filter for high-attenuation angles (c). Black line in c = reconstruction position.

View larger version (155K): [in a new window]   Figure 13a.  Original axial CT images (top) and coronal reformatted images (bottom) in their original form (a) and after reconstruction with multidimensional adaptive filtration (b). (Courtesy of Willi Kalender, PhD, University of Erlangen, Germany.)

View larger version (151K): [in a new window]   Figure 13b.  Original axial CT images (top) and coronal reformatted images (bottom) in their original form (a) and after reconstruction with multidimensional adaptive filtration (b). (Courtesy of Willi Kalender, PhD, University of Erlangen, Germany.)

View larger version (141K): [in a new window]   Figure 14.  CT image of a Teflon block in a water phantom shows aliasing (arrow) due to undersampling of the edge of the block.

View larger version (160K): [in a new window]   Figure 15a.  CT images of a patient with metal spine implants, reconstructed without any correction (a) and with metal artifact reduction (b). (Courtesy of Siemens, Forchheim, Germany.)

View larger version (146K): [in a new window]   Figure 15b.  CT images of a patient with metal spine implants, reconstructed without any correction (a) and with metal artifact reduction (b). (Courtesy of Siemens, Forchheim, Germany.)

View larger version (92K): [in a new window]   Figure 16.  CT image of the head shows motion artifacts.

View larger version (157K): [in a new window]   Figure 17a.  CT images of the body created with conventional reconstruction (a) and with motion artifact correction (b). (Reprinted, with permission, from reference 3.)

View larger version (156K): [in a new window]   Figure 17b.  CT images of the body created with conventional reconstruction (a) and with motion artifact correction (b). (Reprinted, with permission, from reference 3.)

View larger version (136K): [in a new window]   Figure 18.  CT image of the body obtained with the patient’s arms down but outside the scanning field shows streaking artifacts.

View larger version (23K): [in a new window]   Figure 19.  Formation of a ring artifact when a detector is out of calibration.

View larger version (211K): [in a new window]   Figure 20.  CT image of a water-filled phantom shows ring artifacts.

View larger version (80K): [in a new window]   Figure 21.  Consecutive axial CT images from a helical scan of a cone-shaped phantom lying along the scanner axis. (Reprinted, with permission, from reference 5.)

View larger version (80K): [in a new window]   Figure 22.  Series of CT images from a helical scan of the abdomen shows helical artifacts (arrows). (Reprinted, with permission, from reference 5.)

View larger version (190K): [in a new window]   Figure 23.  CT image of a 12-mm-diameter acrylic sphere supported in air, obtained with 0.6-mm section acquisition and beam pitch of 1.75, shows windmill artifact.

View larger version (16K): [in a new window]   Figure 24a.  (a) Fan beam acquisition as used in single-section scanners. (b) Cone beam acquisition as used in multisection scanners.

View larger version (16K): [in a new window]   Figure 24b.  (a) Fan beam acquisition as used in single-section scanners. (b) Cone beam acquisition as used in multisection scanners.

View larger version (36K): [in a new window]   Figure 25.  Volume of data collected by an outer row of detectors (left) and an inner row (right) on a 16-section scanner.

View larger version (159K): [in a new window]   Figure 26a.  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.

View larger version (158K): [in a new window]   Figure 26b.  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.

View larger version (80K): [in a new window]   Figure 27a.  CT images of a phantom, obtained by using four-section acquisition and standard reconstruction (a), 16-section acquisition and standard reconstruction (b), and 16-section acquisition and cone beam reconstruction (c). (Courtesy of Siemens.)

View larger version (85K): [in a new window]   Figure 27b.  CT images of a phantom, obtained by using four-section acquisition and standard reconstruction (a), 16-section acquisition and standard reconstruction (b), and 16-section acquisition and cone beam reconstruction (c). (Courtesy of Siemens.)

View larger version (77K): [in a new window]   Figure 27c.  CT images of a phantom, obtained by using four-section acquisition and standard reconstruction (a), 16-section acquisition and standard reconstruction (b), and 16-section acquisition and cone beam reconstruction (c). (Courtesy of Siemens.)

View larger version (80K): [in a new window]   Figure 28a.  (a) Sagittal reformatted image from axial CT data obtained with 5-mm collimation and a 5-mm reconstruction interval. (b) Sagittal reformatted image from single-section helical CT data obtained with 5-mm collimation and a 2.5-mm reconstruction interval.

View larger version (76K): [in a new window]   Figure 28b.  (a) Sagittal reformatted image from axial CT data obtained with 5-mm collimation and a 5-mm reconstruction interval. (b) Sagittal reformatted image from single-section helical CT data obtained with 5-mm collimation and a 2.5-mm reconstruction interval.

View larger version (177K): [in a new window]   Figure 29a.  Original axial CT image (a) and coronal reformatted image (b) of the sinuses, obtained with a 16-section scanner by using thin acquisition sections. (Courtesy of Siemens [7].)

View larger version (172K): [in a new window]   Figure 29b.  Original axial CT image (a) and coronal reformatted image (b) of the sinuses, obtained with a 16-section scanner by using thin acquisition sections. (Courtesy of Siemens [7].)

View larger version (113K): [in a new window]   Figure 30.  Maximum intensity projection image obtained with helical CT shows zebra artifacts.