Automatic segmentation of lymphatic perfusion in patients with congenital single ventricle defects
File(s)
Accepted version
Author(s)
Type
Conference Paper
Abstract
The Fontan circulation is the surgical end-point for a variety of singleventricle congenital heart lesions. While recent decades have witnessed substantial improvements in survival rates, the associated physiology remains susceptible to severe complications such as protein-losing enteropathy and plastic bronchitis. These complications are often indicative of abnormal congestion in the lymphatic system, underscoring their significance as harbingers of impending comorbidities. An accurate assessment of congestion severity requires the detailed annotation of lymphatic perfusion patterns in each volumetric scan slice. The manual labelling of such intricate data is time-consuming and demands a high level of expertise, rendering it unfeasible within the confines of standard clinical protocols. We use a curated database consisting of manually annotated T2-weighted magnetic resonance imaging (MRI) scans from 71 Fontan patients post-surgery. Following the current state-of-the-art method for biomedical image segmentation, we evaluate its performance on multiple independent test sets regarding the degree of severity and imaging quality. Incorporating the best-performing model,we have developed a user-friendly interface for the automatic segmentation of lymphatic malformations, which will be published before the conference starts.
Editor(s)
Maier, A
Deserno, TM
Handels, H
Maier-Hein, K
Palm, C
Tolxdorff, T
Date Issued
2024-02-20
Date Acceptance
2024-03-01
Citation
Bildverarbeitung für die Medizin 2024, 2024, pp.255-260
ISBN
978-3-658-44036-7
ISSN
1431-472X
Publisher
Springer Vieweg Verlag
Start Page
255
End Page
260
Journal / Book Title
Bildverarbeitung für die Medizin 2024
Copyright Statement
© 2024 Der/die Autor(en), exklusiv lizenziert an Springer Fachmedien Wiesbaden GmbH, ein Teil von Springer Nature. This is the author’s accepted manuscript made available under a CC-BY licence in accordance with Imperial’s Research Publications Open Access policy (www.imperial.ac.uk/oa-policy)
License URL
Source
German Conference on Medical Image Computing
Subjects
Computer Science
Computer Science, Interdisciplinary Applications
Life Sciences & Biomedicine
Radiology, Nuclear Medicine & Medical Imaging
Science & Technology
Technology
Publication Status
Published
Start Date
2024-03-10
Finish Date
2024-03-12
Coverage Spatial
Erlangen, Germany
Date Publish Online
2024-02-20