Evidence map›Paper›PMID 42747736›Full record

ArticleNeuroinformatics2026

Circle of Willis-Guided Localization for Simultaneous Detection and Classification of Large Vessel Occlusions in Brain CTA.

Valeriia Abramova, Arnau Oliver, Uma M Lal-Trehan Estrada, Rachika E Hamadache, Paola Martínez Arias, Jordi Freixenet, Mikel Terceño, Yolanda Silva, Xavier Lladó

Abstract read
In one paragraph

Article in Neuroinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from 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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Valeriia AbramovaComputer Vision and Robotics Institute, University of Girona, Girona, Catalonia, Spain. valeriia.abramova@udg.edu.
Arnau OliverComputer Vision and Robotics Institute, University of Girona, Girona, Catalonia, Spain.
Uma M Lal-Trehan EstradaComputer Vision and Robotics Institute, University of Girona, Girona, Catalonia, Spain.
Rachika E HamadacheComputer Vision and Robotics Institute, University of Girona, Girona, Catalonia, Spain.
Paola Martínez AriasComputer Vision and Robotics Institute, University of Girona, Girona, Catalonia, Spain.
Jordi FreixenetComputer Vision and Robotics Institute, University of Girona, Girona, Catalonia, Spain.
Mikel TerceñoDepartment of Neurology, Hospital Universitari Dr Josep Trueta - Institut d'Investigació Biomèdica de Girona, Girona, Catalonia, Spain. mterceno.girona.ics@gencat.cat.
Yolanda Silva *Department of Neurology, Hospital Universitari Dr Josep Trueta - Institut d'Investigació Biomèdica de Girona, Girona, Catalonia, Spain.
Xavier Lladó *Computer Vision and Robotics Institute, University of Girona, Girona, Catalonia, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large vessel occlusions (LVOs) are blockages in the brain's major arteries that can cause severe neurological damage. Rapid and accurate detection using computed tomography angiography (CTA) is critical for timely stroke treatment. Here, we present a fully automated approach that detects LVOs and classifies the affected vessel simultaneously. Our method incorporates a spatial prior by using Circle of Willis (CoW) segmentation as additional input, guiding the model to anatomically relevant regions. We evaluated the two strategies, the global approach using the full CTA volume, and the local one focused on CoW regions. Both achieved high performance. Detection sensitivity was 0.97 at 0.20 false positives per image for the global approach, and 0.97 at 0.13 false positives for the local approach. Classification accuracy reached 94% and 91% for global and local strategies, respectively. Importantly, the local approach was 3.3× faster, offering a computationally efficient solution, a critical advantage in acute stroke care, where every minute impacts patient outcomes.

Indexed as

BrainCerebral AngiographyCircle of WillisComputed Tomography AngiographyHumansCircle of willisComputed tomography angiographyLarge vessel occlusionnnDetection

Identifiers

PMID42747736
PMCPMC13582341

What OpenQuestion holds

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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.