Advanced multi-label brain hemorrhage segmentation using an attention-based residual U-Net model

Advanced multi-label brain hemorrhage segmentation using an attention-based residual U-Net model

Abstract Objective This study aimed to develop and assess an advanced Attention-Based Residual U-Net (ResUNet) model for accurately segmenting different types of brain hemorrhages from CT images. The goal was to overcome the limitations of manual segmentation and current automated methods regarding...

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Bibliographic Details
Main Authors: Xinxin Lin, Enmiao Zou, Wenci Chen, Xinxin Chen, Le Lin
Format: Article
Language:English
Published: BMC 2025-07-01
Series:BMC Medical Informatics and Decision Making
Subjects:
CT
Brain hemorrhage
Segmentation
Attention-based residual U-Net
Deep learning
Medical imaging
Online Access:https://doi.org/10.1186/s12911-025-03131-3
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https://doi.org/10.1186/s12911-025-03131-3

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