S-Net: A novel shallow network for enhanced detail retention in medical image segmentation.

Journal: Computer methods and programs in biomedicine
Published Date: Mar 20, 2025

Abstract

BACKGROUND AND OBJECTIVE: In recent years, deep U-shaped network architectures have been widely applied to medical image segmentation tasks, achieving notable successes. However, the inherent limitation of this architecture is that multiple down-sampling lead to significant loss of input image detail information. A series of improvements in skip connections designed to enhance information transfer have not fundamentally resolved the issue. Therefore, we consider retaining information in a simpler and more effective way.

Authors

  • Qinghua Shang
    College of Electronic and Information Engineering, Hebei University, Hebei 071002, PR China.
  • Guanglei Wang
    Key Laboratory of Digital Medical Engineering of Hebei Province, College of Electronic and Information Engineering, Hebei University, Baoding, China.
  • Xihao Wang
    College of Electronic and Information Engineering, Hebei University, Hebei 071002, PR China.
  • Yan Li
    Interdisciplinary Research Center for Biology and Chemistry, Liaoning Normal University, Dalian, China.
  • Hongrui Wang
    School of Integrative Plant Science, Horticulture Section, Cornell AgriTech, Cornell University, Geneva, NY 14456, USA.

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