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App. Res. of Comp. Accepted Paper
Vol. 42, 2025 No. 7

Brain tumor segmentation based on residual mixed attention and adaptive feature fusion

Wu Jinxua,b
Wu Yuna,b
a. State Key Laboratory of Public Big Data, b. College of Computer Science & Technology, Guizhou University, Guiyang 550025, China
DOI: 10.19734/j.issn.1001-3695.2024.10.0432

Abstract

The automated segmentation of brain tumor images is crucial in the auxiliary diagnosis and treatment of brain tumors. This paper proposes a brain tumor segmentation method, RAC-Net(Residual Adaptive Convolutional-Net) , that combines a residual mixed attention mechanism and adaptive feature fusion to address the problems of complex and variable lesions in brain tumor images, as well as blurred boundaries between lesions and the background. First, the Dual Dynamic Convolution Enhancement (DDCE) module enhances feature extraction flexibility and improves the adaptability of the model. Then, the Residual Mixed Attention (RMA) module extracts both global and local features from the image. Finally, the Adaptive Feature Fusion Module (AF2M) fuses deep and shallow features in the decoding path, thereby enriching the feature representation. Experiments on the public datasets BraTS2019 and BraTS2021 and cross-dataset validation with BraTS2023 show that RAC-Net outperforms most existing segmentation methods across various metrics, demonstrating its potential for assisting in the diagnosis of clinically relevant brain tumor diseases.

Foundation Support

国家自然科学基金资助项目(62266011)
贵州省科技计划资助项目(黔科合基础-ZK[2022]一般119)
贵州大学研究生创新人才计划项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.10.0432
Publish at: Application Research of Computers Accepted Paper, Vol. 42, 2025 No. 7

Publish History

[2025-03-11] Accepted Paper

Cite This Article

吴进旭, 吴云. 残差混合注意力与自适应特征融合的脑肿瘤分割 [J]. 计算机应用研究, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2024.10.0432. (Wu Jinxu, Wu Yun. Brain tumor segmentation based on residual mixed attention and adaptive feature fusion [J]. Application Research of Computers, 2025, 42 (7). (2025-03-14). https://doi.org/10.19734/j.issn.1001-3695.2024.10.0432. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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