Automatic etiological classification of stroke thrombus digital photographs using a deep learning model

Automatic etiological classification of stroke thrombus digital photographs using a deep learning model

BackgroundEtiological classification of ischemic stroke is fundamental for secondary prevention, but frequently results in undetermined cause. We aimed to develop a Deep Learning (DL)-based model for automatic etiological classification of ischemic stroke using digital images of thrombi retrieved by...

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Main Authors: Álvaro Lucero-Garófano, Alicia Aliena-Valero, Isabel Vielba-Gómez, Irene Escudero-Martínez, Lluís Morales-Caba, Fernando Aparici-Robles, Diana L. Tarruella Hernández, Gerardo Fortea, José I. Tembl, Juan B. Salom, José V. Manjón
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-01-01
Series:Frontiers in Neurology
Subjects:
ischemic stroke
etiology
artificial intelligence
deep learning
segmentation
classification
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1534845/full
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https://www.frontiersin.org/articles/10.3389/fneur.2025.1534845/full

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