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.
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Metrics Over Time
Publication Details
DOI
Publisher
Zenodo
Subfield
Radiology, Nuclear Medicine and Imaging
Field
Medicine
Domain
Health Sciences
Confidence Score
98%
Source
Open Alex
Keywords
Lung SegmentationNeonatalU-Net