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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 3

Super-resolution reconstruction method for MRI images based on feature separation and parameter-free attention mechanism

Zhao Hong
Zhang Runyan
School of Computer Science and Communication, Lanzhou University of Technology, Lanzhou 730050, China
DOI: 10.19734/j.issn.1001-3695.2025.06.0264

Abstract

For magnetic resonance imaging (MRI) , where super-resolution reconstruction often suffers from insufficient detail representation and high computational cost, a Feature Fusion and Parameter-free Attention Network (FFPAN) is proposed to address these issues. The network consists of three parts: shallow feature extraction, deep feature extraction, and image reconstruction. The deep feature extraction includes a Feature Separation Block (FSB) , a Parameter-free Attention (PA) module, and a Generalized Self Attention (GSA) module. The FSB divides image features into high-frequency details and low-frequency global information. The PA module computes image features through convolutions to capture global dependencies between features. Unlike traditional attention mechanisms, PA generates the attention map from the output of convolution layers without learning additional parameters, resulting in low computational cost. The GSA module effectively extracts global or high-frequency information through self-attention combined with residual connections. Experiments were conducted on the public datasets BraTS21 and FastMRI. The results show that, compared with SwinIR, the proposed method reduces the number of parameters by 48.3% while improving PSNR and SSIM by 0.15 dB and 0.0446, respectively. In addition, subjective evaluation indicates that MRI images reconstructed by this network better preserve image details, demonstrating high clinical value.

Foundation Support

国家自然科学基金资助项目(62166025)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.06.0264
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 3

Publish History

[2025-11-18] Accepted Paper

Cite This Article

赵宏, 张润岩. 基于特征融合与无参数注意力机制的MRI图像超分辨率重建方法 [J]. 计算机应用研究, 2026, 43 (3). (2025-11-18). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0264. (Zhao Hong, Zhang Runyan. Super-resolution reconstruction method for MRI images based on feature separation and parameter-free attention mechanism [J]. Application Research of Computers, 2026, 43 (3). (2025-11-18). https://doi.org/10.19734/j.issn.1001-3695.2025.06.0264. )

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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