Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 43, 2026 No. 1
305-312

3D MRI brain tumor segmentation method based on Mamba-UNet architecture

Zhang Ye
Niu Datian
School of Science, Dalian Minzu University, Dalian Liaoning 116000, China
DOI: 10.19734/j.issn.1001-3695.2025.03.0147

Abstract

Accurate segmentation of multimodal MRI brain tumor images is crucial for clinical diagnosis and prognosis assessment of brain cancer. To address the limitations of convolutional neural networks in capturing global contextual information and modeling long-range dependencies, this paper proposed a novel segmentation model named Polyhedron Conv-Tri-orientated Mamba(PhC-ToMamba) by integrating Mamba with a U-Net architecture. It embedded a Tri-orientated Mamba(ToM) modu-le in the bottleneck layer to model high-dimensional global features by computing and interacting dependencies along three directions, thereby enhancing global feature representation in 3D medical images. In addition, this paper introduced a novel Polyhedron Convolution(PhConv) into the encoder to enlarge the receptive field and improved the extraction of critical target regions. These modules effectively enhanced global context awareness and focused attention on key tumor regions. Extensive experiments were conducted on the BraTS 2021 and MSD Task01_BrainTumor datasets. The proposed PhC-ToMamba achieves Dice scores of 95.05% / 90.46%, 94.53%/89.91%, and 90.74%/75.91% for whole tumor, tumor core, and enhancing tumor segmentation, respectively. Compared with state-of-the-art methods, PhC-ToMamba demonstrates superior segmentation accuracy and parameter efficiency, providing a robust solution for brain tumor segmentation and improving diagnostic precision.

Foundation Support

国家自然科学基金资助项目(11872145)
辽宁省教育厅基本科研资助项目(JYTMS20231805)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.03.0147
Publish at: Application Research of Computers Printed Article, Vol. 43, 2026 No. 1
Section: Technology of Graphic & Image
Pages: 305-312
Serial Number: 1001-3695(2026)01-037-0305-08

Publish History

[2025-08-06] Accepted Paper
[2026-01-05] Printed Article

Cite This Article

张野, 牛大田. 基于Mamba-UNet架构的3D MRI脑肿瘤分割方法 [J]. 计算机应用研究, 2026, 43 (1): 305-312. (Zhang Ye, Niu Datian. 3D MRI brain tumor segmentation method based on Mamba-UNet architecture [J]. Application Research of Computers, 2026, 43 (1): 305-312. )

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.

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