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DMRNet: a dynamic multi-scale residual network for Shamrock view and lumbar plexus segmentation.

Haipo Cui1, Yuxiang Wang1, Liangqing Lin2

  • 1School of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai, China.

Computer Assisted Surgery (Abingdon, England)
|June 12, 2026
PubMed
Summary

A new deep learning model, DMRNet, precisely identifies the lumbar plexus in ultrasound images, aiding anesthesiologists in lumbar plexus block (LPB) procedures for hip and knee surgeries.

Keywords:
Biomedical image processingdeep learninglumbar plexusultrasound imaging

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence
  • Anesthesiology

Background:

  • Lumbar plexus block (LPB) is crucial for hip and knee surgeries.
  • Ultrasound guidance is used, but lumbar plexus anatomy presents challenges.
  • Accurate sonoanatomical recognition is vital for effective LPB.

Purpose of the Study:

  • To develop a deep learning model for precise lumbar plexus segmentation in ultrasound images.
  • To assist anesthesiologists in identifying the lumbar plexus in the Shamrock view.
  • To improve the accuracy and efficiency of ultrasound-guided LPB.

Main Methods:

  • Proposed DMRNet, a deep learning model integrating Adaptive Multi-Scale Dilated (AMD) and Dense Attention Residual (DAR) modules.
  • Incorporated Attention-Enhanced Hybrid (AEH) Module and attention mechanisms (BASA, ER-MHA).
  • Trained and evaluated the model on Shamrock view ultrasound images for delineating muscles, nerves, and bony structures.

Main Results:

  • DMRNet achieved a mean Intersection over Union (IoU) of 0.863.
  • DMRNet achieved a mean Dice coefficient of 0.926 across all target structures.
  • The model outperformed existing state-of-the-art segmentation models.

Conclusions:

  • DMRNet demonstrates high accuracy in segmenting sonoanatomical structures in the Shamrock view.
  • The model shows potential as an assistive tool for anesthesiologists during ultrasound-guided LPB.
  • DMRNet can offer educational support for training in ultrasound-guided LPB.