scholarly journals Image Quality of Low-Dose Cerebral Angiography and Effectiveness of Clinical Implementation on Diagnostic and Neurointerventional Procedures for Intracranial Aneurysms

2019 ◽  
Vol 40 (5) ◽  
pp. 827-833 ◽  
Author(s):  
J. Choi ◽  
B. Kim ◽  
Y. Choi ◽  
N.Y. Shin ◽  
J. Jang ◽  
...  
Keyword(s):  
Image Quality ◽  
Cerebral Angiography ◽  
Intracranial Aneurysms ◽  
Low Dose ◽  
Clinical Implementation ◽  
Neurointerventional Procedures

scholarly journals The Use of Artificial Intelligence in Computed Tomography Image Reconstruction: A Systematic Review

2020 ◽  
Vol 4 (2) ◽  
pp. 30-38
Author(s):  
Theresa Lee ◽  
◽  
Euclid Seeram ◽  
Keyword(s):  
Artificial Intelligence ◽  
Computed Tomography ◽  
Image Reconstruction ◽  
Image Quality ◽  
Low Dose ◽  
Ct Imaging ◽  
Clinical Implementation ◽  
Low Dose Ct ◽  
Dose Reductions

Background Current image reconstruction techniques in computed tomography (CT) such as filtered back-projection (FBP) and iterative reconstruction (IR) have limited use in low-dose CT imaging due to poor image quality and reconstruction times not fit for clinical implementation. Hence, with the increasing need for radiation dose reductions in CT, the use of artificial intelligence (AI) in image reconstruction has been an area of growing interest. Aim The aim of this review is to examine the use of AI in CT image reconstruction and its effectiveness in enabling further dose reductions through improvements in image quality of low-dose CT images. Method A review of the literature from 2016 to 2020 was conducted using the databases Scopus, Ovid MEDLINE, and PubMed. A subsequent search of several well-known journals was performed to obtain additional information. After careful assessment, articles were excluded if they were not obtainable from the databases or not available in English. Results This review found that deep learning-based algorithms demonstrate promising results in improving the image quality of low-dose images through noise suppression, artefact reduction, and structure preservation in addition to optimising IR methods. Conclusion In conclusion, with the two AI-based CT systems currently in clinical use showing favourable benefits, it is expected that AI algorithms will continue to proliferate and enable significant dose reductions in CT imaging.

scholarly journals Radiation Dose Optimization in Pediatric Chest CT: Major Indicators of Dose Exposure in 1695 CT Scans over Seven Years

2018 ◽  
Vol 190 (12) ◽  
pp. 1131-1140 ◽  
Author(s):  
Michael Esser ◽  
Sabine Hess ◽  
Matthias Teufel ◽  
Mareen Kraus ◽  
Sven Schneeweiß ◽  
...  
Keyword(s):  
Image Quality ◽  
Radiation Dose ◽  
Low Dose ◽  
Chest Ct ◽  
Dose Optimization ◽  
High Dose ◽  
High Pitch ◽  
Pediatric Chest ◽  
Radiation Dose Optimization

Purpose To analyze possible influencing factors on radiation exposure in pediatric chest CT using different approaches for radiation dose optimization and to determine major indicators for dose development. Materials and Methods In this retrospective study at a clinic with maximum care facilities including pediatric radiology, 1695 chest CT examinations in 768 patients (median age: 10 years; range: 2 days to 17.9 years) were analyzed. Volume CT dose indices, effective dose, size-specific dose estimate, automatic dose modulation (AEC), and high-pitch protocols (pitch ≥ 3.0) were evaluated by univariate analysis. The image quality of low-dose examinations was compared to higher dose protocols by non-inferiority testing. Results Median dose-specific values annually decreased by an average of 12 %. High-pitch mode (n = 414) resulted in lower dose parameters (p < 0.001). In unenhanced CT, AEC delivered higher dose values compared to scans with fixed parameters (p < 0.001). In contrast-enhanced CT, the use of AEC yielded a significantly lower radiation dose only in patients older than 16 years (p = 0.04). In the age group 6 to 15 years, the values were higher (p < 0.001). The diagnostic image quality of low-dose scans was non-inferior to high-dose scans (2.18 vs. 2.14). Conclusion Radiation dose of chest CT was reduced without loss of image quality in the last decade. High-pitch scanning was an independent factor in this context. Dose reduction by AEC was limited and only relevant for patients over 16 years. Key Points Citation Format

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 Improving Image Quality of Medical Low-Dose X-ray Image Sequences Using a Neural Filter

1999 ◽  
Vol 119 (11) ◽  
pp. 1383-1391
Author(s):  
Kenji Suzuki ◽  
Tatsuya Hayashi ◽  
Shigeyuki Ikeda ◽  
Isao Horiba ◽  
Noboru Sugie ◽  
...  
Keyword(s):  
Image Quality ◽  
Low Dose ◽  
Image Sequences ◽  
X Ray ◽  
Neural Filter
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