App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 12

Medical image classification method based on multilevel attention prior-guided diffusion network

Song Yuanbing1a
Wang Wenju1b
Du Yu2
Wu Rong2
Zheng Yi2
1. a. School of Health Science and Engineering, b. College of Publishing, University of Shanghai for Science and Technology, Shanghai 200093, China
2. Dept. of Ultrasound, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
DOI: 10.19734/j.issn.1001-3695.2026.03.0092

Abstract

Objective: Current medical image classification accuracy faces limitations due to the inadequate ability of Convolutional Neural Networks (CNNs) to capture long-range dependencies and global semantic information, alongside the constraints of Transformer architectures in representing low-level local detail features. To improve classification performance, this paper proposes a Multi-level Attention Prior-guided Diffusion Network (MAPDN) . Methods: This study combines ResNet and a Bidirectional Multilayer Perceptron (BMLP) to design a Residual Bidirectional MLP Encoder (RBEncoder) , which reliably encodes the deep semantic features of medical images. Furthermore, this paper constructs a Multi-level Attention Prior Feature Extraction Module (MAEM) to enhance feature representation capabilities and extract richer conditional priors for the diffusion process. The introduction of the diffusion model further optimizes the feature learning and inference processes. Results: This paper evaluates MAPDN on two public datasets (HAM10000 and APTOS2019) and one private dataset (SBC2025) . MAPDN achieves accuracies of 88.3%, 85.2%, and 89.0% on these datasets, respectively. Conclusion: Compared with other deep learning methods, MAPDN achieves state-of-the-art performance, demonstrating the effectiveness of this model in medical image classification tasks.

Foundation Support

国家自然科学基金资助项目(82130057,82572231,82302201)
上海市领军人才计划资助项目(SHLJ-121)
上海市科技启明星计划资助项目(24QA2707500)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.03.0092
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 12

Publish History

[2026-07-29] Accepted Paper

Cite This Article

宋元冰, 王文举, 杜宇, 等. 用于医学图像分类的多层次注意力先验引导扩散模型 [J]. 计算机应用研究, 2026, 43 (12). (2026-08-25). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0092. (Song Yuanbing, Wang Wenju, Du Yu, et al. Medical image classification method based on multilevel attention prior-guided diffusion network [J]. Application Research of Computers, 2026, 43 (12). (2026-08-25). https://doi.org/10.19734/j.issn.1001-3695.2026.03.0092. )

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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