Version V1

Results Dataset - Neonatal MRI Lung Segmentation and 3D Features

Mairhörmann, Benedikt;Castelblanco, Alejandra;Häfner, Friederike;Pfahler, Vanessa;Haist, Lena;Waibel, Dominik;Flemmer, Andreas;Ehrhardt, Harald;Stoecklein, Sophia;Dietrich, Olaf;Foerster, Kai;Hilgendorff, Anne;Schubert, Benjamin

Description

We developed an ensemble of deep convolutional neural networks to automatically and with high consistency perform neonatal lung segmentation from MRI sequences. A 3D representation of the lung were implemented to calculate volumetric features. In addition, ML Models for severity prediction of Bronchopulmonary Dysplasia (BPD) are implemented as an applied example of the use of MRI lung volumetric features for disease prognosis. This dataset comprises the resulting performances and features per MRI-sequence.

Citations (0)

Mentions (0)

Metrics

Dataset Index

0.4

FAIR Score

73%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

Zenodo

License

Creative Commons Attribution 4.0 International

Open Access

Assigned Domain

Subfield

Radiology, Nuclear Medicine and Imaging

Field

Medicine

Domain

Health Sciences

Confidence Score

98%

Source

Open Alex

Keywords

Lung SegmentationNeonatalU-Net

Normalization Factors

FT

57.69

CTw

1.00

MTw

1.00