ArticleComputational intelligence and neuroscience2022
Value of 4D CT Angiography Combined with Whole Brain CT Perfusion Imaging Feature Analysis under Deep Learning in Imaging Examination of Acute Ischemic Stroke.
Article in Computational intelligence and neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it, 8 citations in OpenAlex.
- Machine learning models of segmentation in acute ischemic stroke: a systematic review and meta-analysis.Biomedical engineering online · 2026Pooled it
- Article
- Future Applications of Cardiothoracic CT.Radiology · 2025Review
- Precranial artery calcification burden: a potential indicator of the clinical outcome of reperfusion in patients with acute large artery occlusion.The Journal of international medical research · 2024Observational
- White matter hyperintensities had a correlation with the cerebral perfusion level, but no correlation with the severity of large vessel stenosis in the anterior circulation.Brain and behavior · 2023Article
- Arteriovenous cerebral blood flow correlation in moderate-to-severe traumatic brain injury: CT perfusion study.Brain & spine · 2023Article
- Changes of Arterial and Venous Cerebral Blood Flow Correlation in Moderate-to-Severe Traumatic Brain Injury: A CT Perfusion Study.Advances in experimental medicine and biology · 2023Article
Corrections and comments
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study was aimed at investigating the application of deep learning 4D computed tomography angiography (CTA) combined with whole brain CT perfusion (CTP) imaging in acute ischemic stroke (AIS). A total of 46 patients with ischemic stroke were selected from the hospital as the research objects. Image quality was analyzed after the 4D CTA images were obtained by perfusion imaging. The results showed that whole brain perfusion imaging based on FCN can achieve automatic segmentation. FCN segmentation results took a short time, an average of 2-3 seconds, and the Dice similarity coefficient (DSC) and mean absolute distance (MAD) were lower than those of other algorithms. FCN segmentation distance was 17.87. The parameters of the central area, the peripheral area, and the mirror area of the perfusion map were compared, and the mean transit time (MTT) and time to peak (TTP) of the lesion were prolonged compared with the mirror area. Moreover, the peripheral CBV was increased, and the differences between the parameters were significant (
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