Dense 3D Reconstruction Through Lidar: a New Perspective on Computer-Integrated Surgery

EasyChair Preprint 8113

Abstract

Technical innovations in sensing and computation are quickly advancing the field of computer-integrated surgery. In this fast-evolving panorama, we strongly believe there is still a need for robust geometric reconstruction of the surgical field.

3D reconstruction in surgery has been investigated almost only in the space of mono and stereoscopic visual imaging because surgeons always view the procedure through a clinical endoscope.

Meanwhile, lidar (light detection and ranging) has greatly expanded in use, especially in SLAM for robotics, terrestrial vehicles, and drones.

In parallel to these developments, the concept of multiple-viewpoint surgical imaging was proposed in the early 2010's in the context of magnetic actuation and micro-invasive surgery.

We here propose an approach in which each surgical cannula can potentially hold a miniature lidar.

Direct comparison between lidar from different viewpoints and a state-of-the-art 3D reconstruction method on stereoendoscope images showed that lidar-generated point clouds achieve better accuracy and scene coverage.

This experiment especially hints at the potential of lidar imaging when deployed in a multiple-viewpoint approach.

Keyphrases: 3D reconstruction, Computer-Integrated Surgery, LIDAR sensing

@booklet{EasyChair:8113,
  author    = {Guido Caccianiga and Katherine J. Kuchenbecker},
  title     = {Dense 3D Reconstruction Through Lidar: a New Perspective on Computer-Integrated Surgery},
  howpublished = {EasyChair Preprint 8113},
  year      = {EasyChair, 2022}}