Automatic Ultrasound Image Segmentation of Supraclavicular Nerve Using Dilated U-Net Deep Learning Architecture

TL;DR

This paper presents a deep learning-based automated segmentation system for supraclavicular nerves in ultrasound images, aiming to assist in nerve block procedures and improve regional anesthesia accuracy.

Contribution

Introduces a novel dilated U-Net architecture for nerve segmentation in ultrasound images, enhancing automated recognition for medical applications.

Findings

The dilated U-Net outperforms standard models in nerve detection accuracy.

Automated segmentation reduces reliance on visual recognition by anesthesiologists.

Potential to improve nerve block success rates in clinical practice.

Abstract

Automated object recognition in medical images can facilitate medical diagnosis and treatment. In this paper, we automatically segmented supraclavicular nerves in ultrasound images to assist in injecting peripheral nerve blocks. Nerve blocks are generally used for pain treatment after surgery, where ultrasound guidance is used to inject local anesthetics next to target nerves. This treatment blocks the transmission of pain signals to the brain, which can help improve the rate of recovery from surgery and significantly decrease the requirement for postoperative opioids. However, Ultrasound Guided Regional Anesthesia (UGRA) requires anesthesiologists to visually recognize the actual nerve position in the ultrasound images. This is a complex task given the myriad visual presentations of nerves in ultrasound images, and their visual similarity to many neighboring tissues. In this study, we used an automated nerve detection system for the UGRA Nerve Block treatment. The system can recognize the position of the nerve in ultrasound images using Deep Learning techniques. We developed a model to capture features of nerves by training two deep neural networks with skip connections: two extended U-Net architectures with and without dilated convolutions. This solution could potentially lead to an improved blockade of targeted nerves in regional anesthesia.