A Novel Hybrid Model for Brain Ischemic Stroke Detection Using Feature Fusion and Convolutional Block Attention Module

A Novel Hybrid Model for Brain Ischemic Stroke Detection Using Feature Fusion and Convolutional Block Attention Module

Brain stroke is the second leading cause of death worldwide, following ischemic heart disease. Ischemic stroke occurs when blood vessels are obstructed by a thrombus or other blockages. Prompt and accurate diagnosis of ischemic stroke is critical for patient survival. This study proposes a novel app...

Full description

Saved in:
Bibliographic Details
Main Authors: Ahmad Abumihsan, Amani Yousef Owda, Majdi Owda, Mobarak Abumohsen, Lampros Stergioulas, Mohammad Ahmad Abu Amer
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Brain stroke
computed tomography
feature fusion
convolutional block attention module
MobileNetV3
DenseNet121
Online Access:https://ieeexplore.ieee.org/document/10916628/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/10916628/

Similar Items