Deep learning for standardized, MRI-based quantification of subcutaneous and subfascial tissue volume for patients with lipedema and lymphedema

OBJECTIVES: To contribute to a more in-depth assessment of shape, volume, and asymmetry of the lower extremities in patients with lipedema or lymphedema utilizing volume information from MR imaging. METHODS: A deep learning (DL) pipeline was developed including (i) localization of anatomical landmar...

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Detalles Bibliográficos
Autores principales: Nowak, Sebastian, Henkel, Andreas, Theis, Maike, Luetkens, Julian, Geiger, Sergej, Sprinkart, Alois M., Pieper, Claus C., Attenberger, Ulrike I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Imaging Informatics and Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889496/
https://www.ncbi.nlm.nih.gov/pubmed/35976393
http://dx.doi.org/10.1007/s00330-022-09047-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9889496/
https://www.ncbi.nlm.nih.gov/pubmed/35976393
http://dx.doi.org/10.1007/s00330-022-09047-0

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