Fetal Tissue Annotation and Segmentation Challenge (FeTA), MICCAI 2024

The Fetal Tissue Annotation and Segmentation Challenge (FeTA) is a multi-class, multi-institution image segmentation challenge part of MICCAI 2024. The goal of FeTA is to develop effective, domain-generalizable and reproducible methods for analyzing high resolution reconstructed MR images of the developing fetal brain from gestational week 21-36. The challenge provides manually annotated, super-resolution reconstructed MRI data of human fetal brains which will be used for training and testing automated multi-class image segmentation algorithms.

In FeTA 2021, we used the first publicly available dataset of fetal brain MRI to encourage teams to develop automatic brain tissue segmentation algorithms. FeTA 2022 takes it to the next level by launching a multi-center challenge for the development of image segmentation algorithms that will be generalizable to different hospitals with unseen data. This year, FeTA 2024 includes a new clinically relevant task on automated biometry measurements and data from five different sites and magnetic fields including recent low-field systems.

Such new algorithms will have the potential to contribute to our understanding of the developing normal and pathological human brain across hospitals and research institutions worldwide.

To participate, please click on 'Join' in the menu at the top.

Data Release: 

The complete dataset for the FeTA 2024 Challenge will be released soon. Please follow our  Instructions on how to access it can be found under 'Data Download'.

Program: 

This year, FeTA challenge will be held jointly with the PIPPI (Perinatal, Preterm and Paediatric Image analysis ) workshop. Detailed program for the workshop and challenge will be announced soon on the 'Program' page.

Important Dates:

Data Release: May 2024

Docker Submission Deadline: TBD

Algorithm Description Deadline:  TBD

Notification of Presentations to top teams:  TBD

FeTA 2024 Challenge Day: 6 Oct 2024

For more information, please refers to MICCAI 2024 homepage

Acknowledgements

The project was supported by the Hasler Foundation (Kelly Payette), the University Research Priority Program "Adaptive Brain Circuits in Development and Learning (AdaBD)" (Andras Jakab), the Novartis Foundation for Medical-Biological Research and the Prof.  Max Cloetta Foundation (Andras Jakab), and the Swiss National Science Foundation (215641) and the ERA-NET Neuron MULTI-FACT project (SNSF 31NE30 203977) (Meritxell Bach Cuadra).

Reference

Please cite the following when using the FeTA dataset in your research:
Payette, K., de Dumast, P., Kebiri, H. et al. An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset. Sci Data 8, 167 (2021). https://doi.org/10.1038/s41597-021-00946-3