Automated MRI Lung Segmentation and 3D Morphologic Features for Quantification of Neonatal Lung Disease-Reference-Cited by-同舟云学术

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Automated MRI Lung Segmentation and 3D Morphologic Features for Quantification of Neonatal Lung Disease

Published:2023-11-01 Issue:6 Volume:5 Page:
ISSN:2638-6100
Container-title:Radiology: Artificial Intelligence
language:en
Short-container-title:Radiology: Artificial Intelligence

Author:

Mairhörmann Benedikt^ORCID,Castelblanco Alejandra^ORCID,Häfner Friederike^ORCID,Koliogiannis Vanessa,Haist Lena^ORCID,Winter Dominik,Flemmer Andreas,Ehrhardt Harald^ORCID,Stöcklein Sophia^ORCID,Dietrich Olaf^ORCID,Förster Kai^ORCID,Hilgendorff Anne^ORCID,Schubert Benjamin

Funder

Helmholtz Zentrum München

Deutsches Zentrum für Lungenforschung

German Network for Bioinformatics Infrastructure

Publisher

Radiological Society of North America (RSNA)

Subject

Artificial Intelligence,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Link

http://pubs.rsna.org/doi/pdf/10.1148/ryai.220239

Reference40 articles.

1. Bronchopulmonary Dysplasia

2. Lung CT Image Segmentation Using Deep Neural Networks

3. Bronchopulmonary dysplasia

4. Clinical prediction models for bronchopulmonary dysplasia: a systematic review and external validation study

5. Mechanisms of Lung Injury and Bronchopulmonary Dysplasia

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Don’t Forget the Kids!: Novel Pulmonary MRI and AI of Neonatal Lung Disease;Radiology: Artificial Intelligence;2023-11-01

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