ArticleEuropean radiology2023
Automated unruptured cerebral aneurysms detection in TOF MR angiography images using dual-channel SE-3D UNet: a multi-center research.
Article in European radiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- A Landmark-Guided Dual-Stream Synergistic Framework for Automated Intracranial Aneurysm Detection in Magnetic Resonance Angiography.Journal of imaging informatics in medicine · 2026Article
- Automated segmentation and quantitative analysis of vascular curvature features in unruptured intracranial aneurysms based on time-of-flight magnetic resonance angiography (TOF-MRA).Quantitative imaging in medicine and surgery · 2026Article
- Multi-centric AI Model for Unruptured Intracranial Aneurysm Detection and Volumetric Segmentation in 3D TOF-MRI.Journal of imaging informatics in medicine · 2026Article
- Effectiveness of psychological intervention based on implicit theory combined with virtual reality in patients with unruptured intracranial aneurysm receiving their first cerebral angiography after flow-diverter stent implantation.Frontiers in psychiatry · 2026Article
- TFDFNet: a dual-branch fault diagnosis model for bearings under noisy and complex industrial environments.Scientific reports · 2025Article
- Deep learning model for automated diagnosis of moyamoya disease based on magnetic resonance angiography.EClinicalMedicine · 2024Article
- Global trend in research of intracranial aneurysm management with artificial intelligence technology: a bibliometric analysis.Quantitative imaging in medicine and surgery · 2024Article
- Advances in research and application of artificial intelligence and radiomic predictive models based on intracranial aneurysm images.Frontiers in neurology · 2024Review
- A multi-center performance assessment for automated histopathological classification and grading of glioma using whole slide images.iScience · 2023Article
- Role of artificial intelligence and machine learning in the diagnosis of cerebrovascular disease.Frontiers in human neuroscience · 2023Review
- Utilizing conditional generative adversarial network to generate head MRA based on nonvascular sequences: comparative study of single-modality and multi-modality methods.Frontiers in neurologyArticle
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Authors and funding
12 authors at 5 institutions in 2 countries.
Funding
Abstract
objectivesTime of flight magnetic resonance angiography (TOF-MRA) is the primary non-invasive screening method for cerebral aneurysms. We aimed to develop a computer-aided aneurysm detection method to improve the diagnostic efficiency and accuracy, especially decrease the false positive rate.
methodsThis is a retrospective multicenter study. The dataset contained 1160 TOF-MRA examinations composed of unruptured aneurysms (n = 1096) and normal controls (n = 166) from six hospitals. A total of 1037 examinations acquired from 2013 to 2019 were used as training set; 123 examinations acquired from 2020 to 2021 were used as external test set. We proposed an equalized augmentation strategy based on aneurysm location and constructed a detection model based on dual channel SE-3D UNet. The model was trained with a 5-fold cross-validation in the training set, then tested on the external test set.
resultsThe proposed method achieved 82.46% sensitivity on patient-level, 73.85% sensitivity on lesion-level, and 0.88 false positives per case in the external test set. The performance did not show significant differences in subgroups according to the aneurysm site (except ACA), aneurysm size (except smaller than 3 mm), or MRI scanners. The performance preceded the basic SE-3D UNet by increasing 15.79% patient-level sensitivity and decreasing 4.19 FPs/case.
conclusionsThe proposed automated aneurysm detection method achieved acceptable sensitivity while controlling fairly low false positives per case. It might provide a useful auxiliary tool of cerebral aneurysms MRA screening. KEY POINTS: • The need for automated cerebral aneurysms detecting is growing. • The strategy of equalized augmentation based on aneurysm location and dual-channel input could improve the model performance. • The retrospective multi-center study showed that the proposed automated cerebral aneurysms detection using dual-channel SE-3D UNet could achieve acceptable sensitivity while controlling a low false positive rate.
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