SU-GG-J-30: A Novel Scatter Reduction and Correction Method to Improve Cone-Beam CT (CBCT) Image Quality

2010 ◽  
Vol 37 (6Part9) ◽  
pp. 3151-3151
Author(s):  
L Ren ◽  
J Kim ◽  
Q Liu ◽  
B Movsas ◽  
I Chetty ◽  
...  
Keyword(s):  
Image Quality ◽  
Cone Beam Ct ◽  
Correction Method ◽  
Cone Beam ◽  
Cbct Image ◽  
Scatter Reduction

Dose and Image Quality Evaluation of a Dedicated Cone-Beam CT System for High-Contrast Neurologic Applications

2010 ◽  
Vol 194 (2) ◽  
pp. W193-W201 ◽  
Author(s):  
Lifeng Yu ◽  
Thomas J. Vrieze ◽  
Michael R. Bruesewitz ◽  
James M. Kofler ◽  
David R. DeLone ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Evaluation ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
High Contrast ◽  
Image Quality Evaluation ◽  
Ct System

A 3D printed phantom for Image Quality Assessment in Cone-beam CT

2018 ◽  
Vol 52 ◽  
pp. 170
Author(s):  
James O’Halloran ◽  
Paddy Gilligan ◽  
Sinead Cleary ◽  
Susan Maguire ◽  
Gerald O’Connor ◽  
...  
Keyword(s):  
Image Quality ◽  
Quality Assessment ◽  
Image Quality Assessment ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
3D Printed

Improved image quality of cone beam CT scans for radiotherapy image guidance using fiber-interspaced antiscatter grid

2014 ◽  
Vol 41 (6Part1) ◽  
pp. 061910 ◽  
Author(s):  
Uros Stankovic ◽  
Marcel van Herk ◽  
Lennert S. Ploeger ◽  
Jan-Jakob Sonke
Keyword(s):  
Image Quality ◽  
Image Guidance ◽  
Cone Beam Ct ◽  
Ct Scans ◽  
Cone Beam ◽  
Antiscatter Grid

scholarly journals Effect of metal artifact reduction software on image quality of C-arm cone-beam computed tomography during intracranial aneurysm treatment

2018 ◽  
Vol 24 (3) ◽  
pp. 303-308 ◽  
Author(s):  
Yukiko Enomoto ◽  
Keita Yamauchi ◽  
Takahiko Asano ◽  
Katharina Otani ◽  
Toru Iwama
Keyword(s):  
Computed Tomography ◽  
Image Quality ◽  
Intracranial Aneurysms ◽  
Clinical Findings ◽  
Cone Beam ◽  
Artifact Reduction ◽  
Metal Artifact ◽  
Metal Artifact Reduction ◽  
Cbct Image

Background and purpose C-arm cone-beam computed tomography (CBCT) has the drawback that image quality is degraded by artifacts caused by implanted metal objects. We evaluated whether metal artifact reduction (MAR) prototype software can improve the subjective image quality of CBCT images of patients with intracranial aneurysms treated with coils or clips. Materials and methods Forty-four patients with intracranial aneurysms implanted with coils (40 patients) or clips (four patients) underwent one CBCT scan from which uncorrected and MAR-corrected CBCT image datasets were reconstructed. Three blinded readers evaluated the image quality of the image sets using a four-point scale (1: Excellent, 2: Good, 3: Poor, 4: Bad). The median scores of the three readers of uncorrected and MAR-corrected images were compared with the paired Wilcoxon signed-rank and inter-reader agreement of change scores was assessed by weighted kappa statistics. The readers also recorded new clinical findings, such as intracranial hemorrhage, air, or surrounding anatomical structures on MAR-corrected images. Results The image quality of MAR-corrected CBCT images was significantly improved compared with the uncorrected CBCT image ( p < 0.001). Additional clinical findings were seen on CBCT images of 70.4% of patients after MAR correction. Conclusion MAR software improved image quality of CBCT images degraded by metal artifacts.

scholarly journals Relationship between CNR and visibility of anatomical structures of cone-beam computed tomography images under different exposure parameters

2020 ◽  
Vol 49 (5) ◽  
pp. 20190336
Author(s):  
Miss Fei Wang ◽  
Xiaoyan Xie ◽  
Gang Li ◽  
Zuyan Zhang
Keyword(s):  
Image Quality ◽  
Change Point ◽  
Cone Beam Ct ◽  
Cone Beam ◽  
Physical Factors ◽  
Anatomical Structures ◽  
Subjective Image Quality ◽  
Computed Tomography Images ◽  
Tissue Equivalent ◽  
Imagej Software

Objectives: The purpose of this study was to investigate the image quality of cone beam CT (CBCT) under different exposure parameters and the relationship between contrast-to-noise and visibility of eight anatomical structures. Methods: CBCT images for the evaluation of subjective image quality were acquired on an anthropopathic phantom containing a human skeleton embedded in soft tissue equivalent materials using 25 exposure protocols. Visibility of eight anatomical structures was evaluated by five independent observers. Using the SEDENTEXCT IQ Image Quality phantom, the contrast-to-noise ratio (CNR) was calculated by ImageJ software. Results: A reduction on the visibility of anatomical structures was seen under lower exposure parameters. However, for 84% of the protocols, visibility of anatomical structures remained acceptable even under some lower parameter settings. As CNR increased, the visibility of anatomical structures also increased correspondingly. A change point could be found in the CNR interval 29.42–36.51 after which the visibility of anatomical structures no longer increases with the increase of CNR. Conclusions: Although CNR decrease under a lower exposure parameter, the image quality often remained acceptable at exposure levels below the manufacture’s recommended settings. It is possible to standardize subjective image quality by physical factors. Currently, it is not possible to predetermine a change point CNR value due to different CBCT machine and variation of diagnostic tasks.

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