Graph convolution-based adaptive feature fusion method for MRI brain tumor segmentation

Graph convolution-based adaptive feature fusion method for MRI brain tumor segmentation

To address the issues of insufficient global information capture and inadequate deep semantic information fusion in the U-Net model for MRI brain tumor segmentation,a novel brain tumor segmentation network,ASGU-Net was proposed. The algorithm was based on 3D U-Net,incorporating a graph convolution i...

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Bibliographic Details
Main Authors: Ye ZHANG, Muqing ZHANG, Xuegang YUAN, Datian NIU
Format: Article
Language:zho
Published: Hebei University of Science and Technology 2025-08-01
Series:Journal of Hebei University of Science and Technology
Subjects:
computer neural network; brain tumor segmentation; 3d u-net; graph convolution inference bottleneck layer; dynamic snake convolution; adaptive spatial feature fusion
Online Access:https://xuebao.hebust.edu.cn/hbkjdx/article/pdf/b202504005?st=article_issue
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https://xuebao.hebust.edu.cn/hbkjdx/article/pdf/b202504005?st=article_issue

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