Technology of Graphic & Image
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 3
895-899,905

Improved lung nodules segmentation algorithm based on WU-Net

Zhang Yujie
Ye Xining
College of Information Science & Engineering, East China University of Science & Technology, Shanghai 200237, China
DOI: 10.19734/j.issn.1001-3695.2021.07.0292

Abstract

Deep convolutional neural network is widely used in the field of medical image segmentation. In recent years, multi-scale fusion structure is used to improve segmentation network, which often increases the complexity of the model and reduces the training efficiency while improving the accuracy. To solve these problems, this paper proposed a novel segmentation algorithm for WU-Net pulmonary nodules. It improved the U-Net by introducing an improved residual connection module into the original down-sampling coding channel and mean while using the information channel improved by the new dep module to complete feature extraction and feature fusion. In the experiment, it used LUNA16 dataset to train and verify the model. Meanwhile, comparative experiments used some newly segmentation models. In the experiment with scale of nodules, the Dice coefficient and IoU of proposed model can reach 96.72% and 91.78% respectively. F1-score can reach 92.41% after adding 10% negative samples, which is 1.23% higher than UNet3+. In the experiment with scale of lung parenchyma, the Dice coefficient and IoU of proposed model can reach 83.33% and 66.79% respectively, which is 1.35% and 2.53% higher than RU-Net. The training efficiency of WU-Net is the highest, which is 39.6% higher than U-Net spend. The result shows that WU-Net has improved segmentation effects and training efficiency of model as well.

Foundation Support

国家自然科学基金资助项目(60974066)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.07.0292
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 3
Section: Technology of Graphic & Image
Pages: 895-899,905
Serial Number: 1001-3695(2022)03-044-0895-05

Publish History

[2021-11-06] Accepted Paper
[2022-03-05] Printed Article

Cite This Article

张宇杰, 叶西宁. 基于WU-Net网络的肺结节图像分割算法 [J]. 计算机应用研究, 2022, 39 (3): 895-899,905. (Zhang Yujie, Ye Xining. Improved lung nodules segmentation algorithm based on WU-Net [J]. Application Research of Computers, 2022, 39 (3): 895-899,905. )

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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