Robust fetoscopic mosaicking from deep learned flow fields.

ABSTRACT:

Purpose

Fetoscopic laser photocoagulation is a minimally invasive procedure to treat twin-to-twin transfusion syndrome during pregnancy by stopping irregular blood flow in the placenta. Building an image mosaic of the placenta and its network of vessels could assist surgeons to navigate in the challenging fetoscopic environment during the procedure.

Methodology

We propose a fetoscopic mosaicking approach by combining deep learning-based optical flow with robust estimation for filtering inconsistent motions that occurs due to floating particles and specularities. While the current state of the art for fetoscopic mosaicking relies on clearly visible vessels for registration, our approach overcomes this limitation by considering the motion of all consistent pixels within consec

SUBMITTER: Alabi O 

PROVIDER: S-EPMC9124660 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature