Inpainting surgical occlusion from laparoscopic video sequences for robot-assisted interventions.

ABSTRACT:

Purpose

Medical technology for minimally invasive surgery has undergone a paradigm shift with the introduction of robot-assisted surgery. However, it is very difficult to track the position of the surgical tools in a surgical scene, so it is crucial to accurately detect and identify surgical tools. This task can be aided by deep learning-based semantic segmentation of surgical video frames. Furthermore, due to the limited working and viewing areas of these surgical instruments, there is a higher chance of complications from tissue injuries (e.g., tissue scars and tears).

Approach

With the aid of digital inpainting algorithms, we present an application that uses image segmentation to remove surgical instruments from laparoscopic/endoscopic video. We employ a modified U-Net ar

SUBMITTER: Hasan SMK 

PROVIDER: S-EPMC10462486 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature