Stable image registration for in-vivo fetoscopic panorama reconstruction

Journal article (2018)

Authors

F. Gaisser Intelligent Vehicles - Mechanical, Maritime and Materials Engineering
Suzanne H.P. Peeters Universiteit Leiden
B.A.J. Lenseigne Biomechanical Engineering
P.P. Jonker Biomechatronics & Human-Machine Control - Mechanical, Maritime and Materials Engineering
D. Oepkes Universiteit Leiden
Research Group
Intelligent Vehicles (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2018 F. Gaisser, Suzanne H.P. Peeters, B.A.J. Lenseigne, P.P. Jonker, Dick Oepkes
DOI
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https://doi.org/10.3390/jimaging4010024
Panorama reconstruction In-vivo fetoscopy Stable region detection
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Published Date

2018

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Intelligent Vehicles

Abstract

A Twin-to-Twin Transfusion Syndrome (TTTS) is a condition that occurs in about 10% of pregnancies involving monochorionic twins. This complication can be treated with fetoscopic laser coagulation. The procedure could greatly benefit from panorama reconstruction to gain an overview of the placenta. In previous work we investigated which steps could improve the reconstruction performance for an in-vivo setting. In this work we improved this registration by proposing a stable region detection method as well as extracting matchable features based on a deep-learning approach. Finally, we extracted a measure for the image registration quality and the visibility condition. With experiments we show that the image registration performance is increased and more constant. Using these methods a system can be developed that supports the surgeon during the surgery, by giving feedback and providing a more complete overview of the placenta.