CRANet: a comprehensive residual attention network for intracranial aneurysm image classification

CRANet: a comprehensive residual attention network for intracranial aneurysm image classification

Abstract Rupture of intracranial aneurysm is the first cause of subarachnoid hemorrhage, second only to cerebral thrombosis and hypertensive cerebral hemorrhage, and the mortality rate is very high. MRI technology plays an irreplaceable role in the early detection and diagnosis of intracranial aneur...

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Bibliographic Details
Main Authors:	Yawu Zhao, Shudong Wang, Yande Ren, Yulin Zhang
Format:	Article
Language:	English
Published:	BMC 2022-08-01
Series:	BMC Bioinformatics
Subjects:	Medical image classification Deep residual learning Comprehensive attention mechanism
Online Access:	https://doi.org/10.1186/s12859-022-04872-y

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