Automatic Annotations by Augmented Reality‐Enabled Laparoscopic Surgery
Alexander Winkler, Christian Heiliger, Thomas Heiliger, Ulrich Eck, Konrad Karcz, Nassir Navab

TL;DR
This paper introduces a system that automatically generates surgical annotations using augmented reality, reducing the need for manual labeling by medical experts.
Contribution
A novel method for automatic surgical annotation generation using AR-enabled spatial and temporal registration during laparoscopic surgery.
Findings
The AR system can generate structured labels from synchronized multimodal data streams during surgery.
The system can create annotations even when visual input is occluded or out of camera view.
User evaluations confirmed the feasibility and usability of the AR-based annotation system.
Abstract
Accurate labels of surgical procedures such as image segmentations or interaction labels are paramount for many of today's medical image computing tasks. Creating a dataset with these labels requires a great deal of manual work and relies on the involvement of medical experts, which is very time‐consuming and costly. We propose a pathway for the automatic generation of such labels utilizing the spatial and temporal registration between a patient, the anatomical model, tracked surgical instruments, and the surgeon's view of the patient. These requirements for the automatic generation of labels are identical to the requirements of many navigated and augmented reality (AR) enabled surgeries. The AR system, through 3D registration, has the defining ability to accurately overlay real objects with their virtual counterparts. Our approach collects the complete raw data (e.g. video, tracking…
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Taxonomy
TopicsAugmented Reality Applications · Surgical Simulation and Training · Medical Image Segmentation Techniques
