FETAL_PLANES_DB: Common maternal-fetal ultrasound images
Burgos-Artizzu, Xavier P. and Coronado-Gutierrez, David and Valenzuela-Alcaraz, Brenda and Bonet-Carne, Elisenda and Eixarch, Elisenda and Crispi, Fatima and Gratacós, Eduard

@article{zenodo_3904280,
title= {FETAL_PLANES_DB: Common maternal-fetal ultrasound images},
journal= {},
author= {Burgos-Artizzu, Xavier P. and Coronado-Gutierrez, David and Valenzuela-Alcaraz, Brenda and Bonet-Carne, Elisenda and Eixarch, Elisenda and Crispi, Fatima and Gratacós, Eduard},
year= {2020},
url= {https://zenodo.org/records/3904280},
abstract= {A large dataset of routinely acquired maternal-fetal screening ultrasound images collected from two different hospitals by several operators and ultrasound machines. All images were manually labeled by an expert maternal fetal clinician. Images are divided into 6 classes: four of the most widely used fetal anatomical planes (Abdomen, Brain, Femur and Thorax), the mother’s cervix (widely used for prematurity screening) and a general category to include any other less common image plane. Fetal brain images are further categorized into the 3 most common fetal brain planes (Trans-thalamic, Trans-cerebellum, Trans-ventricular) to judge fine grain categorization performance. Meta information (patient number, us machine, operator) is also provided, as well as the training-test split used in the Nature Sci Rep paper.

**Paper:** Burgos-Artizzu XP, et al. Evaluation of deep convolutional neural networks for automatic classification of common maternal fetal ultrasound planes. Scientific Reports 10, 10200 (2020). https://doi.org/10.1038/s41598-020-67076-5

**License:** CC BY 4.0. Source: https://zenodo.org/records/3904280},
files= {FETAL_PLANES_ZENODO.zip},
keywords= {ultrasound, Medical imaging, fetal images},
license= {https://creativecommons.org/licenses/by/4.0/},
terms= {},
superseded= {}
}