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Titel:

Automated assessment of cardiac pathologies on cardiac MRI using T1-mapping and late gadolinium phase sensitive inversion recovery sequences with deep learning.

Dokumenttyp:
Journal Article
Autor(en):
Paciorek, Aleksandra M; von Schacky, Claudio E; Foreman, Sarah C; Gassert, Felix G; Gassert, Florian T; Kirschke, Jan S; Laugwitz, Karl-Ludwig; Geith, Tobias; Hadamitzky, Martin; Nadjiri, Jonathan
Abstract:
BACKGROUND: A deep learning (DL) model that automatically detects cardiac pathologies on cardiac MRI may help streamline the diagnostic workflow. To develop a DL model to detect cardiac pathologies on cardiac MRI T1-mapping and late gadolinium phase sensitive inversion recovery (PSIR) sequences were used. METHODS: Subjects in this study were either diagnosed with cardiac pathology (n = 137) including acute and chronic myocardial infarction, myocarditis, dilated cardiomyopathy, and hypertrophic c...     »
Zeitschriftentitel:
BMC Med Imaging
Jahr:
2024
Band / Volume:
24
Heft / Issue:
1
Volltext / DOI:
doi:10.1186/s12880-024-01217-4
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/38350900
TUM Einrichtung:
Institut für Diagnostische und Interventionelle Radiologie (Prof. Makowski)
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