ArticleDiagnostics (Basel, Switzerland)2023
Accuracy of Dose-Saving Artificial-Intelligence-Based 3D Angiography (3DA) for Grading of Intracranial Artery Stenoses: Preliminary Findings.
Article in Diagnostics (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Calculation of virtual 3D subtraction angiographies using conditional generative adversarial networks (cGANs).BMC medical imaging · 2024Article
- Comparison of computer-aided quantitative measurement and physician visual assessment in the evaluation of intracranial atherosclerotic stenosis: a vessel wall magnetic resonance imaging study.Quantitative imaging in medicine and surgery · 2024Article
- [Opportunities for artificial intelligence in radiation protection : Improving safety of diagnostic imaging].Radiologie (Heidelberg, Germany) · 2023Review
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Authors and funding
9 authors.
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Abstract
background and purposeBased on artificial intelligence (AI), 3D angiography (3DA) is a novel postprocessing algorithm for "DSA-like" 3D imaging of cerebral vasculature. Because 3DA requires neither mask runs nor digital subtraction as the current standard 3D-DSA does, it has the potential to cut the patient dose by 50%. The object was to evaluate 3DA's diagnostic value for visualization of intracranial artery stenoses (IAS) compared to 3D-DSA. MATERIALS AND
methods3D-DSA datasets of IAS (n
resultsIn total, 20 angiographic 3D volumes (n
conclusionsThe AI-based 3DA is a resilient algorithm for the visualization of IAS and shows comparable results to 3D-DSA. Hence, 3DA is a promising new method that allows a considerable patient-dose reduction, and its clinical implementation would be highly desirable.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.