skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

Abstract

Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. Formore » the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.« less

Authors:
; ; ; ; ;  [1]
  1. Southern Medical University, Guangzhou, Guangdong (China)
Publication Date:
OSTI Identifier:
22626780
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ACCURACY; BIOMEDICAL RADIOGRAPHY; COMPUTERIZED TOMOGRAPHY; CORRECTIONS; IMAGE PROCESSING; IMAGES; INTERPOLATION; PHANTOMS; SIMULATION; SPATIAL RESOLUTION

Citation Formats

Yuan, C, Qi, H, Chen, Z, Wu, S, Xu, Y, and Zhou, L. SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image. United States: N. p., 2016. Web. doi:10.1118/1.4955836.
Yuan, C, Qi, H, Chen, Z, Wu, S, Xu, Y, & Zhou, L. SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image. United States. doi:10.1118/1.4955836.
Yuan, C, Qi, H, Chen, Z, Wu, S, Xu, Y, and Zhou, L. Wed . "SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image". United States. doi:10.1118/1.4955836.
@article{osti_22626780,
title = {SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image},
author = {Yuan, C and Qi, H and Chen, Z and Wu, S and Xu, Y and Zhou, L},
abstractNote = {Purpose: In computed tomography (CT) system, CT images with ring artifacts will be reconstructed when some adjacent bins of detector don’t work. The ring artifacts severely degrade CT image quality. We present a useful CT ring artifacts reduction based on projection data correction, aiming at estimating the missing data of projection data accurately, thus removing the ring artifacts of CT images. Methods: The method consists of ten steps: 1) Identification of abnormal pixel line in projection sinogram; 2) Linear interpolation within the pixel line of projection sinogram; 3) FBP reconstruction using interpolated projection data; 4) Filtering FBP image using mean filter; 5) Forwarding projection of filtered FBP image; 6) Subtraction forwarded projection from original projection; 7) Linear interpolation of abnormal pixel line area in the subtraction projection; 8) Adding the interpolated subtraction projection on the forwarded projection; 9) FBP reconstruction using corrected projection data; 10) Return to step 4 until the pre-set iteration number is reached. The method is validated on simulated and real data to restore missing projection data and reconstruct ring artifact-free CT images. Results: We have studied impact of amount of dead bins of CT detector on the accuracy of missing data estimation in projection sinogram. For the simulated case with a resolution of 256 by 256 Shepp-Logan phantom, three iterations are sufficient to restore projection data and reconstruct ring artifact-free images when the dead bins rating is under 30%. The dead-bin-induced artifacts are substantially reduced. More iteration number is needed to reconstruct satisfactory images while the rating of dead bins increases. Similar results were found for a real head phantom case. Conclusion: A practical CT image ring artifact correction scheme based on projection data is developed. This method can produce ring artifact-free CT images feasibly and effectively.},
doi = {10.1118/1.4955836},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}
  • Purpose: To optimize adult head CT protocol by reducing dose to an appropriate level while providing CT images of diagnostic quality. Methods: Five cadavers were scanned from the skull base to the vertex using a routine adult head CT protocol (120 kVp, 270 mA, 0.75 s rotation, 0.5 mm × 32 detectors, 70.8 mGy CTDIvol) followed by seven reduced-dose protocols with varying combinations of reduced tube current, reduced rotation time, and increased detectors with CTDIvol ranging from 38.2 to 65.6 mGy. Organ doses were directly measured with 21 OSL dosimeters placed on the surface and implanted in the head bymore » a neurosurgeon. Two neuroradiologists assessed grey-white matter differentiation, fluid space, ventricular size, midline shift, brain mass, edema, ischemia, and skull fractures on a three point scale: (1) Unacceptable, (2) Borderline Acceptable, and (3) Acceptable. Results: For the standard scan, doses to the skin, lens of the eye, salivary glands, thyroid, and brain were 37.55 mGy, 49.65 mGy, 40.67 mGy, 4.63 mGy, and 27.33 mGy, respectively. Two cadavers had cerebral edema due to changing dynamics of postmortem effects, causing the grey-white matter differentiation to appear less distinct. Two cadavers with preserved grey-white matter received acceptable scores for all image quality features for the protocol with a CTDIvol of 57.3 mGy, allowing organ dose savings ranging from 34% to 45%. One cadaver allowed for greater dose reduction for the protocol with a CTDIvol of 42 mGy. Conclusion: Efforts to optimize scan protocol should consider both dose and clinical image quality. This is made possible with postmortem subjects, whose brains are similar to patients, allowing for an investigation of ideal scan parameters. Radiologists at our institution accepted scan protocols acquired with lower scan parameters, with CTDIvol values closer to the American College of Radiology’s (ACR) Achievable Dose level of 57 mGy.« less
  • Purpose: To present a simple method for quantification of dual-energy CT metal artifact reduction capabilities Methods: A phantom was constructed from solid water and a steel cylinder. Solid water is commonly used for radiotherapy QA, while steel cylinders are readily available in hardware stores. The phantom was scanned on Siemens Somatom 64-slice dual-energy CT system. Three CTs were acquired at energies of 80kV (low), 120kV (nominal), and 140kV (high). The low and high energy acquisitions were used to generate dual-energy (DE) monoenergetic image sets, which also utilized metal artifact reduction algorithm (Maris). Several monoenergetic DE image sets, ranging from 70keVmore » to 190keV were generated. The size of the metal artifact was measured by two different approaches. The first approach measured the distance from the center of the steel cylinder to a location with nominal (undisturbed by metal) HU value for the 120kV, DE 70keV, and DE 190keV image sets. In the second approach, the distance from the center of the cylinder to the edge of the air pocket for the above mentioned three image sets was measured. Results: The DE 190keV synthetic image set demonstrated the largest reduction of the metal artifacts. The size of the artifact was more than three times the actual size of the milled hole in the solid water in the DE 190keV, as compared to more than 7.5 times larger as estimated from the 120kV uncorrected image Conclusion: A simple phantom for quantification of dual-energy CT metal artifact reduction capabilities was presented. This inexpensive phantom can be easily built from components available in every radiation oncology department. It allows quick assessment and quantification of the properties of different metal artifact reduction algorithms, available on modern dual-energy CT scanners.« less
  • Purpose: Accuracy of radiotherapy dose calculation in patients with surgical implants is complicated by two factors. First is the accuracy of CT number, second is the dose calculation accuracy. We compared measured dose with dose calculated on CT images reconstructed with FBP and an artifact reduction algorithm (OMAR, Philips) for a phantom with high density inserts. Dose calculation were done with Varian AAA and AcurosXB. Methods: A phantom was constructed with solid water in which 2 titanium or stainless steel rods could be inserted. The phantom was scanned with the Philips Brillance Big Bore CT. Image reconstruction was done withmore » FBP and OMAR. Two 6 MV single field photon plans were constructed for each phantom. Radiochromic films were placed at different locations to measure the dose deposited. One plan has normal incidence on the titanium/steel rods. In the second plan, the beam is at almost glancing incidence on the metal rods. Measurements were then compared with dose calculated with AAA and AcurosXB. Results: The use of OMAR images slightly improved the dose calculation accuracy. The agreement between measured and calculated dose was best with AXB and image reconstructed with OMAR. Dose calculated on titanium phantom has better agreement with measurement. Large discrepancies were seen at points directly above and below the high density inserts. Both AAA and AXB underestimated the dose directly above the metal surface, while overestimated the dose below the metal surface. Doses measured downstream of metal were all within 3% of calculated values. Conclusion: When doing treatment planning for patients with metal implants, care must be taken to acquire correct CT images to improve dose calculation accuracy. Moreover, great discrepancies in measured and calculated dose were observed at metal/tissue interface. Care must be taken in estimating the dose in critical structures that come into contact with metals.« less
  • Purpose: CT simulation for patients with metal implants can often be challenging due to artifacts that obscure tumor/target delineation and normal organ definition. Our objective was to evaluate the effectiveness of Orthopedic Metal Artifact Reduction (OMAR), a commercially available software, in reducing metal-induced artifacts and its effect on computed dose during treatment planning. Methods: CT images of water surrounding metallic cylindrical rods made of aluminum, copper and iron were studied in terms of Hounsfield Units (HU) spread. Metal-induced artifacts were characterized in terms of HU/Volume Histogram (HVH) using the Pinnacle treatment planning system. Effects of OMAR on enhancing our abilitymore » to delineate organs on CT and subsequent dose computation were examined in nine (9) patients with hip implants and two (2) patients with breast tissue expanders. Results: Our study characterized water at 1000 HU with a standard deviation (SD) of about 20 HU. The HVHs allowed us to evaluate how the presence of metal changed the HU spread. For example, introducing a 2.54 cm diameter copper rod in water increased the SD in HU of the surrounding water from 20 to 209, representing an increase in artifacts. Subsequent use of OMAR brought the SD down to 78. Aluminum produced least artifacts whereas Iron showed largest amount of artifacts. In general, an increase in kVp and mA during CT scanning showed better effectiveness of OMAR in reducing artifacts. Our dose analysis showed that some isodose contours shifted by several mm with OMAR but infrequently and were nonsignificant in planning process. Computed volumes of various dose levels showed <2% change. Conclusions: In our experience, OMAR software greatly reduced the metal-induced CT artifacts for the majority of patients with implants, thereby improving our ability to delineate tumor and surrounding organs. OMAR had a clinically negligible effect on computed dose within tissues. Partially funded by unrestricted educational grant from Philips.« less
  • Purpose: A new commercially available metal artifact reduction (MAR) software in computed tomography (CT) imaging was evaluated with phantoms in the presence of metals. The goal was to assess the ability of the software to restore the CT number in the vicinity of the metals without impacting the image quality. Methods: A Catphan 504 was scanned with a GE Optima RT 580 CT scanner (GE Healthcare, Milwaukee, WI) and the images were reconstructed with and without the MAR software. Both datasets were analyzed with Image Owl QA software (Image Owl Inc, Greenwich, NY). CT number sensitometry, MTF, low contrast, uniformity,more » noise and spatial accuracy were compared for scans with and without MAR software. In addition, an in-house made phantom was scanned with and without a stainless steel insert at three different locations. The accuracy of the CT number and metal insert dimension were investigated as well. Results: Comparisons between scans with and without MAR algorithm on the Catphan phantom demonstrate similar results for image quality. However, noise was slightly higher for the MAR algorithm. Evaluation of the CT number at various locations of the in-house made phantom was also performed. The baseline HU, obtained from the scan without metal insert, was compared to scans with the stainless steel insert at 3 different locations. The HU difference between the baseline scan versus metal scan was improved when the MAR algorithm was applied. In addition, the physical diameter of the stainless steel rod was over-estimated by the MAR algorithm by 0.9 mm. Conclusion: This work indicates with the presence of metal in CT scans, the MAR algorithm is capable of providing a more accurate CT number without compromising the overall image quality. Future work will include the dosimetric impact on the MAR algorithm.« less