Clinical feasibility of deep learning-driven magnetic resonance angiography collateral map in acute anterior circulation ischemic stroke

Clinical feasibility of deep learning-driven magnetic resonance angiography collateral map in acute anterior circulation ischemic stroke

Abstract To validate the clinical feasibility of deep learning-driven magnetic resonance angiography (DL-driven MRA) collateral map in acute ischemic stroke. We employed a 3D multitask regression and ordinal regression deep neural network, called as 3D-MROD-Net, to generate DL-driven MRA collateral...

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Bibliographic Details
Main Authors: Ye Jin Jeon, Hong Gee Roh, Sumin Jung, Hyun Yang, Hee Jong Ki, Jeong Jin Park, Taek-Jun Lee, Na Il Shin, Ji Sung Lee, Jin Tae Kwak, Hyun Jeong Kim
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Scientific Reports
Subjects:
Cerebrovascular disorders
Stroke
Collateral circulation
Deep learning
Magnetic resonance imaging
Artificial intelligence
Online Access:https://doi.org/10.1038/s41598-025-85731-7
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https://doi.org/10.1038/s41598-025-85731-7

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