3D surgical instrument collection for computer vision and extended reality

Abstract

The availability of computational hardware and developments in (medical) machine learning (MML) increases medical mixed realities’ (MMR) clinical usability. Medical instruments have played a vital role in surgery for ages. To further accelerate the implementation of MML and MMR, three-dimensional (3D) datasets of instruments should be publicly available. The proposed data collection consists of 103, 3D-scanned medical instruments from the clinical routine, scanned with structured light scanners. The collection consists, for example, of instruments, like retractors, forceps, and clamps. The collection can be augmented by generating likewise models using 3D software, resulting in an inflated dataset for analysis. The collection can be used for general instrument detection and tracking in operating room settings, or a freeform marker-less instrument registration for tool tracking in augmented reality. Furthermore, for medical simulation or training scenarios in virtual reality and medical diminishing reality in mixed reality. We hope to ease research in the field of MMR and MML, but also to motivate the release of a wider variety of needed surgical instrument datasets.

Publication
Scientific Data
Gijs Luijten
Gijs Luijten
PhD Student
Jens Kleesiek
Jens Kleesiek
Professor of Translational Image-guided Oncology
Jan Egger
Jan Egger
Team Lead AI-guided Therapies