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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. 2016. "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 = 2016,
month = 6
}
  • Purpose: To evaluate the metal artifacts in kilovoltage computed tomography (kVCT) images that are corrected using a normalized metal artifact reduction (NMAR) method with megavoltage CT (MVCT) prior images.Methods: Tissue characterization phantoms containing bilateral steel inserts are used in all experiments. Two MVCT images, one without any metal artifact corrections and the other corrected using a modified iterative maximum likelihood polychromatic algorithm for CT (IMPACT) are translated to pseudo-kVCT images. These are then used as prior images without tissue classification in an NMAR technique for correcting the experimental kVCT image. The IMPACT method in MVCT included an additional model formore » the pair/triplet production process and the energy dependent response of the MVCT detectors. An experimental kVCT image, without the metal inserts and reconstructed using the filtered back projection (FBP) method, is artificially patched with the known steel inserts to get a reference image. The regular NMAR image containing the steel inserts that uses tissue classified kVCT prior and the NMAR images reconstructed using MVCT priors are compared with the reference image for metal artifact reduction. The Eclipse treatment planning system is used to calculate radiotherapy dose distributions on the corrected images and on the reference image using the Anisotropic Analytical Algorithm with 6 MV parallel opposed 5 × 10 cm{sup 2} fields passing through the bilateral steel inserts, and the results are compared. Gafchromic film is used to measure the actual dose delivered in a plane perpendicular to the beams at the isocenter.Results: The streaking and shading in the NMAR image using tissue classifications are significantly reduced. However, the structures, including metal, are deformed. Some uniform regions appear to have eroded from one side. There is a large variation of attenuation values inside the metal inserts. Similar results are seen in commercially corrected image. Use of MVCT prior images without tissue classification in NMAR significantly reduces these problems. The radiation dose calculated on the reference image is close to the dose measured using the film. Compared to the reference image, the calculated dose difference in the conventional NMAR image, the corrected images using uncorrected MVCT image, and IMPACT corrected MVCT image as priors is ∼15.5%, ∼5%, and ∼2.7%, respectively, at the isocenter.Conclusions: The deformation and erosion of the structures present in regular NMAR corrected images can be largely reduced by using MVCT priors without tissue segmentation. The attenuation value of metal being incorrect, large dose differences relative to the true value can result when using the conventional NMAR image. This difference can be significantly reduced if MVCT images are used as priors. Reduced tissue deformation, better tissue visualization, and correct information about the electron density of the tissues and metals in the artifact corrected images could help delineate the structures better, as well as calculate radiation dose more correctly, thus enhancing the quality of the radiotherapy treatment planning.« less
  • Purpose: To evaluate the metal artifacts in diagnostic kVCT images of patients that are corrected using a normalized metal artifact reduction method with MVCT prior images, MVCT-NMAR. Methods: An MVCTNMAR algorithm was developed and applied to five patients: three with bilateral hip prostheses, one with unilateral hip prosthesis and one with dental fillings. The corrected images were evaluated for visualization of tissue structures and their interfaces, and for radiotherapy dose calculations. They were also compared against the corresponding images corrected by a commercial metal artifact reduction technique, O-MAR, on a Phillips™ CT scanner. Results: The use of MVCT images formore » correcting kVCT images in the MVCT-NMAR technique greatly reduces metal artifacts, avoids secondary artifacts, and makes patient images more useful for correct dose calculation in radiotherapy. These improvements are significant over the commercial correction method, provided the MVCT and kVCT images are correctly registered. The remaining and the secondary artifacts (soft tissue blurring, eroded bones, false bones or air pockets, CT number cupping within the metal) present in O-MAR corrected images are removed in the MVCT-NMAR corrected images. Large dose reduction is possible outside the planning target volume (e.g., 59.2 Gy in comparison to 52.5 Gy in pubic bone) when these MVCT-NMAR corrected images are used in TomoTherapy™ treatment plans, as the corrected images no longer require directional blocks for prostate plans in order to avoid the image artifact regions. Conclusion: The use of MVCT-NMAR corrected images in radiotherapy treatment planning could improve the treatment plan quality for cancer patients with metallic implants. Moti Raj Paudel is supported by the Vanier Canada Graduate Scholarship, the Endowed Graduate Scholarship in Oncology and the Dissertation Fellowship at the University of Alberta. The authors acknowledge the CIHR operating grant number MOP 53254.« less
  • Purpose: To evaluate the metal artifacts in diagnostic kilovoltage computed tomography (kVCT) images of patients that are corrected by use of a normalized metal artifact reduction (NMAR) method with megavoltage CT (MVCT) prior images: MVCT-NMAR. Methods and Materials: MVCT-NMAR was applied to images from 5 patients: 3 with dual hip prostheses, 1 with a single hip prosthesis, and 1 with dental fillings. The corrected images were evaluated for visualization of tissue structures and their interfaces and for radiation therapy dose calculations. They were compared against the corresponding images corrected by the commercial orthopedic metal artifact reduction algorithm in a Phillipsmore » CT scanner. Results: The use of MVCT images for correcting kVCT images in the MVCT-NMAR technique greatly reduces metal artifacts, avoids secondary artifacts, and makes patient images more useful for correct dose calculation in radiation therapy. These improvements are significant, provided the MVCT and kVCT images are correctly registered. The remaining and the secondary artifacts (soft tissue blurring, eroded bones, false bones or air pockets, CT number cupping within the metal) present in orthopedic metal artifact reduction corrected images are removed in the MVCT-NMAR corrected images. A large dose reduction was possible outside the planning target volume (eg, 59.2 Gy to 52.5 Gy in pubic bone) when these MVCT-NMAR corrected images were used in TomoTherapy treatment plans without directional blocks for a prostate cancer patient. Conclusions: The use of MVCT-NMAR corrected images in radiation therapy treatment planning could improve the treatment plan quality for patients with metallic implants.« less
  • Purpose: Image quality in computed tomography (CT) often suffers from artifacts which may reduce the diagnostic value of the image. In many cases, these artifacts result from missing or corrupt regions in the projection data, e.g., in the case of metal, truncation, and limited angle artifacts. The authors propose a generalized correction method for different kinds of artifacts resulting from missing or corrupt data by making use of available prior knowledge to perform data completion. Methods: The proposed prior-based artifact correction (PBAC) method requires prior knowledge in form of a planning CT of the same patient or in form ofmore » a CT scan of a different patient showing the same body region. In both cases, the prior image is registered to the patient image using a deformable transformation. The registered prior is forward projected and data completion of the patient projections is performed using smooth sinogram inpainting. The obtained projection data are used to reconstruct the corrected image. Results: The authors investigate metal and truncation artifacts in patient data sets acquired with a clinical CT and limited angle artifacts in an anthropomorphic head phantom data set acquired with a gantry-based flat detector CT device. In all cases, the corrected images obtained by PBAC are nearly artifact-free. Compared to conventional correction methods, PBAC achieves better artifact suppression while preserving the patient-specific anatomy at the same time. Further, the authors show that prominent anatomical details in the prior image seem to have only minor impact on the correction result. Conclusions: The results show that PBAC has the potential to effectively correct for metal, truncation, and limited angle artifacts if adequate prior data are available. Since the proposed method makes use of a generalized algorithm, PBAC may also be applicable to other artifacts resulting from missing or corrupt data.« less
  • Purpose: Image quality in computed tomography (CT) often suffers from artifacts which may reduce the diagnostic value of the image. In many cases, these artifacts result from missing or corrupt regions in the projection data, e.g., in the case of metal, truncation, and limited angle artifacts. The authors propose a generalized correction method for different kinds of artifacts resulting from missing or corrupt data by making use of available prior knowledge to perform data completion. Methods: The proposed prior-based artifact correction (PBAC) method requires prior knowledge in form of a planning CT of the same patient or in form ofmore » a CT scan of a different patient showing the same body region. In both cases, the prior image is registered to the patient image using a deformable transformation. The registered prior is forward projected and data completion of the patient projections is performed using smooth sinogram inpainting. The obtained projection data are used to reconstruct the corrected image. Results: The authors investigate metal and truncation artifacts in patient data sets acquired with a clinical CT and limited angle artifacts in an anthropomorphic head phantom data set acquired with a gantry-based flat detector CT device. In all cases, the corrected images obtained by PBAC are nearly artifact-free. Compared to conventional correction methods, PBAC achieves better artifact suppression while preserving the patient-specific anatomy at the same time. Further, the authors show that prominent anatomical details in the prior image seem to have only minor impact on the correction result. Conclusions: The results show that PBAC has the potential to effectively correct for metal, truncation, and limited angle artifacts if adequate prior data are available. Since the proposed method makes use of a generalized algorithm, PBAC may also be applicable to other artifacts resulting from missing or corrupt data.« less