Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies

Validation of body composition parameters extracted via deep learning-based segmentation from routine computed tomographies

Abstract Sarcopenia and body composition metrics are strongly associated with patient outcomes. In this study, we developed and validated a flexible, open-access pipeline integrating available deep learning-based segmentation models with pre- and postprocessing steps to extract body composition meas...

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Bibliographic Details
Main Authors: Felix O. Hofmann, Christian Heiliger, Tengis Tschaidse, Stefanie Jarmusch, Liv A. Auhage, Ughur Aghamaliyev, Alena B. Gesenhues, Tobias S. Schiergens, Hanno Niess, Matthias Ilmer, Jens Werner, Bernhard W. Renz
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Body composition
Computed tomography
Sarcopenia
Tissue segmentation
Oncology
Online Access:https://doi.org/10.1038/s41598-025-96238-6
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https://doi.org/10.1038/s41598-025-96238-6

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