Learning feature descriptors for pre- and intra-operative point cloud matching for laparoscopic liver registration.

ABSTRACT:

Purpose

In laparoscopic liver surgery, preoperative information can be overlaid onto the intra-operative scene by registering a 3D preoperative model to the intra-operative partial surface reconstructed from the laparoscopic video. To assist with this task, we explore the use of learning-based feature descriptors, which, to our best knowledge, have not been explored for use in laparoscopic liver registration. Furthermore, a dataset to train and evaluate the use of learning-based descriptors does not exist.

Methods

We present the LiverMatch dataset consisting of 16 preoperative models and their simulated intra-operative 3D surfaces. We also propose the LiverMatch network designed for this task, which outputs per-point feature descriptors, visibility scores, and matched points

SUBMITTER: Yang Z 

PROVIDER: S-EPMC10330103 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature