ArticleKorean journal of radiology2019
Application of Vendor-Neutral Iterative Reconstruction Technique to Pediatric Abdominal Computed Tomography.
Article in Korean journal of radiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Low-contrast-dose liver CT using low monoenergetic images with deep learning-based denoising for assessing hepatocellular carcinoma: a randomized controlled noninferiority trial.European radiology · 2023Trial
- Additional Dose Reduction Potential of Vendor-Agnostic Deep Learning Model: A Phantom Study.Journal of the Korean Society of Radiology · 2026Article
- Diagnostic performance of lumbar spine CT using deep learning denoising to evaluate disc herniation and spinal stenosis.European radiology · 2025Article
- Agreement between Routine-Dose and Lower-Dose CT with and without Deep Learning-based Denoising for Active Surveillance of Solid Small Renal Masses: A Multiobserver Study.Radiology. Imaging cancer · 2025Article
- Evaluation of a Vendor-Agnostic Deep Learning Model for Noise Reduction and Image Quality Improvement in Dental CBCT.Diagnostics (Basel, Switzerland) · 2024Article
- Diagnostic performance and image quality of an image-based denoising algorithm applied to radiation dose-reduced CT in diagnosing acute appendicitis.Abdominal radiology (New York) · 2024Article
- Enhanced visualization in endoleak detection through iterative and AI-noise optimized spectral reconstructions.Scientific reports · 2024Article
- Ultra-low-dose computed tomography with deep learning reconstruction for craniosynostosis at radiation doses comparable to skull radiographs: a pilot study.Pediatric radiology · 2023Article
- Ultra-low-dose CT is feasible for torsion measurement of the lower limb in patients with metal implants.The British journal of radiology · 2023Article
- Radiation dose reduction using deep learning-based image reconstruction for a low-dose chest computed tomography protocol: a phantom study.Quantitative imaging in medicine and surgery · 2023Article
- The Impact of Novel Reconstruction Algorithms on Calcium Scoring: Results on a Dedicated Cardiac CT Scanner.Diagnostics (Basel, Switzerland) · 2023Article
- Fully automated image quality evaluation on patient CT: Multi-vendor and multi-reconstruction study.PloS one · 2022Article
- Article
- Deep Learning Algorithm for Simultaneous Noise Reduction and Edge Sharpening in Low-Dose CT Images: A Pilot Study Using Lumbar Spine CT.Korean journal of radiology · 2021Article
- Image quality assessment of pediatric chest and abdomen CT by deep learning reconstruction.BMC medical imaging · 2021Article
- Advances in deep learning for computed tomography denoising.World journal of clinical cases · 2021Article
- Image quality of ultralow-dose chest CT using deep learning techniques: potential superiority of vendor-agnostic post-processing over vendor-specific techniques.European radiology · 2021Article
- Noise reduction approach in pediatric abdominal CT combining deep learning and dual-energy technique.European radiology · 2021Article
- Incremental Image Noise Reduction in Coronary CT Angiography Using a Deep Learning-Based Technique with Iterative Reconstruction.Korean journal of radiology · 2020Article
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Authors and funding
9 authors.
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Abstract
objectiveTo compare image qualities between vendor-neutral and vendor-specific hybrid iterative reconstruction (IR) techniques for abdominopelvic computed tomography (CT) in young patients. MATERIALS AND
methodsIn phantom study, we used an anthropomorphic pediatric phantom, age-equivalent to 5-year-old, and reconstructed CT data using traditional filtered back projection (FBP), vendor-specific and vendor-neutral IR techniques (ClariCT; ClariPI) in various radiation doses. Noise, low-contrast detectability and subjective spatial resolution were compared between FBP, vendor-specific (i.e., iDose1 to 5; Philips Healthcare), and vendor-neutral (i.e., ClariCT1 to 5) IR techniques in phantom. In 43 patients (median, 14 years; age range 1-19 years), noise, contrast-to-noise ratio (CNR), and qualitative image quality scores of abdominopelvic CT were compared between FBP, iDose level 4 (iDose4), and ClariCT level 2 (ClariCT2), which showed most similar image quality to clinically used vendor-specific IR images (i.e., iDose4) in phantom study. Noise, CNR, and qualitative imaging scores were compared using one-way repeated measure analysis of variance.
resultsIn phantom study, ClariCT2 showed noise level similar to iDose4 (14.68-7.66 Hounsfield unit [HU] vs. 14.78-6.99 HU at CT dose index volume range of 0.8-3.8 mGy). Subjective low-contrast detectability and spatial resolution were similar between ClariCT2 and iDose4. In clinical study, ClariCT2 was equivalent to iDose4 for noise (14.26-17.33 vs. 16.01-18.90) and CNR (3.55-5.24 vs. 3.20-4.60) (
conclusionVendor-neutral IR technique shows image quality similar to that of clinically used vendor-specific hybrid IR technique for abdominopelvic CT in young patients.
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