Model-based medicine and intelligent operating room
Prof. Dr. Thomas Neumuth
The SurgiTrace project aims to develop an intelligent, AI-supported system for effective resource planning during surgical procedures. It addresses the complex perioperative processes and the high demands placed on quality assurance in surgery. A key focus is on the planning and preparation of operations, in particular the loading of the operating theatre trolley with all the necessary utensils such as surgical instruments, materials and implants. This work step is currently carried out by trained operating theatre staff. Due to the numerous disruptive factors such as a lack of time or hectic pace, there is the potential for invasive sources of error. However, as the quality-assured assembly of these materials is essential for a smooth process and patient safety, an intelligent system is to be developed to monitor the process.
To overcome these challenges, SurgiTrace combines the technologies of inductive near-field localisation and optical image analysis, supported by artificial intelligence (AI). This includes accurately verifying the completeness of the required OR resources and determining the exact product type, size and number of components. This system is designed to operate independently of the availability or expertise of medical staff.
The SurgiTrace system consists of two main components: Firstly, the development of an AI-supported tracking process for surgical instruments, based on inductive near-field localisation and image analysis, implemented by Picoba Solutions GmbH. Secondly, the development and integration of a machine learning model for material planning, realised by Leipzig University Medicine – ICCAS. This software supports the planning of the necessary materials for operations by integrating guidelines and clinic-specific procedures. Close collaboration with the medical experts at Leipzig University Hospital (Clinic for Orthopaedics, Trauma Surgery and Plastic Surgery) also enables a practice-relevant development process, which is monitored at regular intervals with the help of evaluation studies.