An End-to-End Deep Learning Framework for Predicting Hematoma Expansion in Hemorrhagic Stroke Patients from CT Images

An End-to-End Deep Learning Framework for Predicting Hematoma Expansion in Hemorrhagic Stroke Patients from CT Images

Hematoma expansion (HE) occurs in 20% of patients with hemorrhagic stroke within 24 h of onset, and it is associated with a poorer patient outcome. From a clinical point of view, predicting HE from the initial patient computed tomography (CT) image is useful to improve therapeutic decisions and mini...

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Bibliographic Details
Main Authors: Valeriia Abramova, Arnau Oliver, Joaquim Salvi, Mikel Terceño, Yolanda Silva, Xavier Lladó
Format: Article
Language:English
Published: MDPI AG 2024-03-01
Series:Applied Sciences
Subjects:
hemorrhagic stroke
hematoma expansion
deep learning
hemorrhage growth prediction
Online Access:https://www.mdpi.com/2076-3417/14/7/2708

Internet

https://www.mdpi.com/2076-3417/14/7/2708

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