DCAU-Net: dense convolutional attention U-Net for segmentation of intracranial aneurysm images

DCAU-Net: dense convolutional attention U-Net for segmentation of intracranial aneurysm images

Abstract Segmentation of intracranial aneurysm images acquired using magnetic resonance angiography (MRA) is essential for medical auxiliary treatments, which can effectively prevent subarachnoid hemorrhages. This paper proposes an image segmentation model based on a dense convolutional attention U-...

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Bibliographic Details
Main Authors: Wenwen Yuan, Yanjun Peng, Yanfei Guo, Yande Ren, Qianwen Xue
Format: Article
Language:English
Published: SpringerOpen 2022-03-01
Series:Visual Computing for Industry, Biomedicine, and Art
Subjects:
Deep learning
Intracranial aneurysm segmentation
Magnetic resonance angiography
Multi-scale fusion
Online Access:https://doi.org/10.1186/s42492-022-00105-4

Internet

https://doi.org/10.1186/s42492-022-00105-4

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