FetReg: Placental Vessel Segmentation and Registration in Fetoscopy
Challenge Dataset
- URL: http://arxiv.org/abs/2106.05923v1
- Date: Thu, 10 Jun 2021 17:14:27 GMT
- Title: FetReg: Placental Vessel Segmentation and Registration in Fetoscopy
Challenge Dataset
- Authors: Sophia Bano, Alessandro Casella, Francisco Vasconcelos, Sara Moccia,
George Attilakos, Ruwan Wimalasundera, Anna L. David, Dario Paladini, Jan
Deprest, Leonardo S. Mattos, Danail Stoyanov
- Abstract summary: Fetoscopy laser photocoagulation is a widely used procedure for the treatment of Twin-to-Twin Transfusion Syndrome (TTTS)
This may lead to increased procedural time and incomplete ablation, resulting in persistent TTTS.
Computer-assisted intervention may help overcome these challenges by expanding the fetoscopic field of view through video mosaicking and providing better visualization of the vessel network.
We present a large-scale multi-centre dataset for the development of generalized and robust semantic segmentation and video mosaicking algorithms for the fetal environment with a focus on creating drift-free mosaics from long duration fetoscopy videos.
- Score: 57.30136148318641
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Fetoscopy laser photocoagulation is a widely used procedure for the treatment
of Twin-to-Twin Transfusion Syndrome (TTTS), that occur in mono-chorionic
multiple pregnancies due to placental vascular anastomoses. This procedure is
particularly challenging due to limited field of view, poor manoeuvrability of
the fetoscope, poor visibility due to fluid turbidity, variability in light
source, and unusual position of the placenta. This may lead to increased
procedural time and incomplete ablation, resulting in persistent TTTS.
Computer-assisted intervention may help overcome these challenges by expanding
the fetoscopic field of view through video mosaicking and providing better
visualization of the vessel network. However, the research and development in
this domain remain limited due to unavailability of high-quality data to encode
the intra- and inter-procedure variability. Through the Fetoscopic Placental
Vessel Segmentation and Registration (FetReg) challenge, we present a
large-scale multi-centre dataset for the development of generalized and robust
semantic segmentation and video mosaicking algorithms for the fetal environment
with a focus on creating drift-free mosaics from long duration fetoscopy
videos. In this paper, we provide an overview of the FetReg dataset, challenge
tasks, evaluation metrics and baseline methods for both segmentation and
registration. Baseline methods results on the FetReg dataset shows that our
dataset poses interesting challenges, which can be modelled and competed for
through our crowd-sourcing initiative of the FetReg challenge.
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