Deep Learning-Based Aortic Diameter Measurement in Traumatic Hemorrhage Using Shallow Attention Network: A Path Forward

Deep Learning-Based Aortic Diameter Measurement in Traumatic Hemorrhage Using Shallow Attention Network: A Path Forward

<b>Background/Objectives:</b> The accurate assessment of aortic diameter (AoD) is essential in managing patients with traumatic hemorrhage, particularly during interventions such as resuscitative endovascular balloon occlusion of the aorta (REBOA). Manual AoD measurements are time-consum...

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Bibliographic Details
Main Authors: Yoonjung Heo, Go-Eun Lee, Jungchan Cho, Sang-Il Choi
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Diagnostics
Subjects:
aorta
trauma
hemorrhage
computed tomography
deep learning
image segmentation
Online Access:https://www.mdpi.com/2075-4418/15/11/1312
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