Features of Service-Oriented Architecture Implementation in the System for Recurrent Laryngeal Nerve Identification

The identification of the recurrent laryngeal nerve (RLN) during thyroid surgeries is crucial to prevent postoperative complications. This paper presents the implementation of a service-oriented architecture (SOA) in the RLN identification system, enhancing modularity and scalability. The proposed system integrates electrophysiological stimulation with adaptive signal processing, allowing real-time nerve localization. Recent advancements in mathematical modeling, including Bayesian shape frameworks and deep learning algorithms, are incorporated to improve accuracy. Experimental results demonstrate enhanced reliability, highlighting the potential of SOA in surgical navigation systems.