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Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 41, 2024 No. 8
2554-2560

Parallel dual-branch image segmentation of skin lesions fusing CNN and Transformer

Tao Xiting
Ye Qing
School of Computer Science, Yangtze University, Jingzhou Hubei 434000, China
DOI: 10.19734/j.issn.1001-3695.2023.10.0600

Abstract

Accurate automatic segmentation of skin lesions is crucial to assist physicians in clinical diagnosis and treatment. Aiming at the problem that convolutional structure can extract local feature information but cannot model long-range dependencies, while Transformer can extract global context information but suffers from the loss of detail information, this paper proposed a parallel multi-scale automatic segmentation network PDTransCNN that integrated CNN and Transformer. Firstly, it constructed multi-level local correlation and captured long-range dependencies between contextual information by extracting the feature information of dermatological images in parallel with the CNN branch based on ResNet34 and Transformer branch. Secondly, it utilized the feature fusion module(FM) to complement the key information between the two branches of features and enhance the dependencies of the semantic information. Finally, it used the Transformer decoding unit to gradually fuse the semantic information extracted from the encoding block and the fusion unit in order to obtain the final segmentation result. The model was tested on ISIC2016, ISIC2017 and ISIC2018 datasets with Dice coefficients as high as 91.72%, 87.34% and 90.01%, and IoU values of 85.60%, 79.55% and 83.67%, respectively. The experimental results show that PDTransCNN has better segmentation performance compared to other segmentation models and can segment skin lesion images clearly and effectively.

Foundation Support

国家自然科学基金资助项目(62006028)
湖北省自然科学基金资助项目(2023AFB909)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.10.0600
Publish at: Application Research of Computers Printed Article, Vol. 41, 2024 No. 8
Section: Technology of Graphic & Image
Pages: 2554-2560
Serial Number: 1001-3695(2024)08-044-2554-07

Publish History

[2024-04-22] Accepted Paper
[2024-08-05] Printed Article

Cite This Article

陶惜婷, 叶青. 融合CNN和Transformer的并行双分支皮肤病灶图像分割 [J]. 计算机应用研究, 2024, 41 (8): 2554-2560. (Tao Xiting, Ye Qing. Parallel dual-branch image segmentation of skin lesions fusing CNN and Transformer [J]. Application Research of Computers, 2024, 41 (8): 2554-2560. )

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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