Abstract
Abstract Tracking of surgical instruments is an essential step towards the modernization of the surgical workflow by a comprehensive surgical landscape guidance system (COMPASS). Real-time tracking of a laparoscopic camera used in minimally-invasive surgery is required for applications in surgical workflow documentation, machine learning, image-localization, and intra-operative visualization. In our approach, an inertial measurement unit (IMU) assists the tool tracking in situations when no line-of-sight is available for infrared (IR) based tracking of the laparoscopic camera. The novelty of this approach lies in the localization method adjusted for the laparoscopic visceral surgery, particularly when the line-of-sight is lost. It is based on IMU tracking and the positioning of the trocar entry point. The trocar entry point is the remote center of motion (RCM), reducing degrees of freedom. We developed a method to tackle localization and a real-time tool for position and orientation estimation. The main error sources are given and evaluated in a test scenario. It reveals that for small changes in penetration length (e.g., pivoting), the IMU’s accuracy determines the error.
Highlights
Tracking of laparoscopic instruments is an application that many researchers focused on to improve surgery in fields like visualization [1], workflow registration, planning, and evaluation
Most concepts rely on overlay technologies that have not been established in visceral surgery since there are fewer applications for guidance as most organs in the abdomen can move freely
We show that orientation and position estimates can be acquired using only an inertial measurement unit (IMU) for timespans where no IR tracking is available and an IR tracking system to find the trocar entry point
Summary
Tracking of laparoscopic instruments is an application that many researchers focused on to improve surgery in fields like visualization [1], workflow registration, planning, and evaluation. We show that orientation and position estimates can be acquired using only an IMU for timespans where no IR tracking is available and an IR tracking system to find the trocar entry point. These results motivate us to conduct further research on multi-sensor fusion. This document, focuses on explaining the algorithm for stable trocar entry point detection and evaluates the prerequisites for and errors of position estimates
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