Application of three-pass metal artifact reduction to photon-counting breast tomosynthesis

2018 ◽  
Author(s):  
Harald S. Heese ◽  
Frank Bergner ◽  
Klaus Erhard ◽  
Artur Sossin ◽  
Björn Cederström ◽  
...  
Keyword(s):  
Photon Counting ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Breast Tomosynthesis

scholarly journals Photon Counting Normalized Metal Artifact Reduction (NMAR) in Diagnostic CT

2021 ◽  
Author(s):  
Achim Byl ◽  
Laura Klein ◽  
Stefan Sawall ◽  
Sarah Heinze ◽  
Heinz‐Peter Schlemmer ◽  
...  
Keyword(s):  
Photon Counting ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Diagnostic Ct

scholarly journals Metal artifact reduction and tumor detection using photon-counting multi-energy computed tomography

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247355
Author(s):  
Chang-Lae Lee ◽  
Junyoung Park ◽  
Sangnam Nam ◽  
Jiyoung Choi ◽  
Yuna Choi ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Photon Counting ◽  
Diagnosis And Treatment ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Metal Artifacts ◽  
Oral Tumor ◽  
Iodine Quantification ◽  
Ct System

Metal artifacts are considered a major challenge in computed tomography (CT) as these adversely affect the diagnosis and treatment of patients. Several approaches have been developed to address this problem. The present study explored the clinical potential of a novel photon-counting detector (PCD) CT system in reducing metal artifacts in head CT scans. In particular, we studied the recovery of an oral tumor region located under metal artifacts after correction. Three energy thresholds were used to group data into three bins (bin 1: low-energy, bin 2: middle-energy, and bin 3: high-energy) in the prototype PCD CT system. Three types of physical phantoms were scanned on the prototype PCD CT system. First, we assessed the accuracy of iodine quantification using iodine phantoms at varying concentrations. Second, we evaluated the performance of material decomposition (MD) and virtual monochromatic images (VMIs) using a multi-energy CT phantom. Third, we designed an ATOM phantom with metal insertions to verify the effect of the proposed metal artifact reduction. In particular, we placed an insertion-mimicking an iodine-enhanced oral tumor in the beam path of metallic objects. Normalized metal artifact reduction (NMAR) was performed for each energy bin image, followed by an image-based MD and VMI reconstruction. Image quality was analyzed quantitatively by contrast-to-noise ratio (CNR) measurements. The results of iodine quantification showed a good match between the true and measured iodine concentrations. Furthermore, as expected, the contrast between iodine and the surrounding material was higher in bin 1 image than in bin 3 image. On the other hand, the bin 3 image of the ATOM phantom showed fewer metal artifacts than the bin 1 image because of the higher photon energy. The result of quantitative assessment demonstrated that the 40-keV VMI (CNR: 20.6 ± 1.2) with NMAR and MD remarkably increased the contrast of the iodine-enhanced region compared with that of the conventional images (CNR: 10.4 ± 0.5) having 30 to 140 keV energy levels. The PCD-based multi-energy CT imaging has immense potential to maximize the contrast of the target tissue and reduce metal artifacts simultaneously. We believe that it would open the door to novel applications for the diagnosis and treatment of several diseases.

scholarly journals A semi-automated quantitative comparison of metal artifact reduction in photon-counting computed tomography by energy-selective thresholding

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
T. D. Do ◽  
S. Sawall ◽  
S. Heinze ◽  
T. Reiner ◽  
C. H. Ziener ◽  
...  
Keyword(s):  
Hip Prosthesis ◽  
Photon Counting ◽  
High Energy ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Metal Artifacts ◽  
Photon Counting Detector ◽  
Concept Images ◽  
Energy Thresholds

AbstractAn evaluation of energy thresholding and acquisition mode for metal artifact reduction in Photon-counting detector CT (PCD-CT) compared to conventional energy-integrating detector CT (EID-CT) was performed. Images of a hip prosthesis phantom placed in a water bath were acquired on a scanner with PCD-CT and EID-CT (tube potentials: 100, 120 and 140 kVp) and energy thresholds (above 55–75 keV) in Macro and Chess mode. Only high-energy threshold images (HTI) were used. Metal artifacts were quantified by a semi-automated segmentation algorithm, calculating artifact volumes, means and standard deviations of CT numbers. Images of a human cadaver with hip prosthesis were acquired on the PCD-CT in Macro mode as proof-of-concept. Images at 140 kVp showed less metal artifacts than 120 kVp or 100 kVp. HTI (70, 75 keV) had fewer artifacts than low energy thresholds (55, 60, 65 keV). Fewer artifacts were observed in the Macro-HTI (8.9–13.3%) for cortical bone compared to Chess-HTI (9.4–19.1%) and EID-CT (10.7–19.0%) whereas in bone marrow Chess-HTI (19.9–45.1%) showed less artifacts compared to Macro-HTI (21.9–38.3%) and EID-CT (36.4–54.9%). Noise for PCD-CT (56–81 HU) was higher than EID-CT (33–36 HU) irrespective of tube potential. High-energy thresholding could be used for metal artifact reduction in PCD-CT, but further investigation of acquisition modes depending on target structure is required.

MR Imaging with Metal Artifact Reduction to Differentiate between Patients with and without Infected Total Hip Arthroplasty

2018 ◽  
Author(s):  
Benedikt Schwaiger ◽  
Alexandra Gersing ◽  
Daniela Muenzel ◽  
Julia Dangelmaier ◽  
Peter Prodinger ◽  
...  
Keyword(s):  
Total Hip Arthroplasty ◽  
Mr Imaging ◽  
Hip Arthroplasty ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Total Hip

Comparison of metal artifact reduction techniques in magnetic resonance imaging of carbon-reinforced PEEK and titanium spinal implants

2021 ◽  
pp. 028418512110290
Author(s):  
Georg Osterhoff ◽  
Florian A Huber ◽  
Laura C Graf ◽  
Ferdinand Erdlen ◽  
Hans-Christoph Pape ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Pedicle Screws ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Signal Loss ◽  
Resonance Imaging ◽  
Spinal Implants ◽  
Titanium Screws

Background Carbon-reinforced PEEK (C-FRP) implants are non-magnetic and have increasingly been used for the fixation of spinal instabilities. Purpose To compare the effect of different metal artifact reduction (MAR) techniques in magnetic resonance imaging (MRI) on titanium and C-FRP spinal implants. Material and Methods Rod-pedicle screw constructs were mounted on ovine cadaver spine specimens and instrumented with either eight titanium pedicle screws or pedicle screws made of C-FRP and marked with an ultrathin titanium shell. MR scans were performed of each configuration on a 3-T scanner. MR sequences included transaxial conventional T1-weighted turbo spin echo (TSE) sequences, T2-weighted TSE, and short-tau inversion recovery (STIR) sequences and two different MAR-techniques: high-bandwidth (HB) and view-angle-tilting (VAT) with slice encoding for metal artifact correction (SEMAC). Metal artifact degree was assessed by qualitative and quantitative measures. Results There was a much stronger effect on artifact reduction with using C-FRP implants compared to using specific MRI MAR-techniques (screw shank: P < 0.001; screw tulip: P < 0.001; rod: P < 0.001). VAT-SEMAC sequences were able to reduce screw-related signal loss artifacts in constructs with titanium screws to a certain degree. Constructs with C-FRP screws showed less artifact-related implant diameter amplification when compared to constructs with titanium screws ( P < 0.001). Conclusion Constructs with C-FRP screws are associated with significantly less artifacts compared to constructs with titanium screws including dedicated MAR techniques. Artifact-reducing sequences are able to reduce implant-related artifacts. This effect is stronger in constructs with titanium screws than in constructs with C-FRP screws.

scholarly journals Metal artifact reduction in computed tomography images based on developed generative adversarial neural network

2021 ◽  
Vol 24 ◽  
pp. 100573
Author(s):  
Goli Khaleghi ◽  
Mohammad Hosntalab ◽  
Mahdi Sadeghi ◽  
Reza Reiazi ◽  
Seied Rabi Mahdavi
Keyword(s):  
Neural Network ◽  
Computed Tomography ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Computed Tomography Images
Sign in / Sign up

Export Citation Format

Share Document