Evaluation of a Deep Learning Algorithm for Automated Spleen Segmentation in Patients with Conditions Directly or Indirectly Affecting the Spleen

The aim of this study was to develop a deep learning-based algorithm for fully automated spleen segmentation using CT images and to evaluate the performance in conditions directly or indirectly affecting the spleen (e.g., splenomegaly, ascites). For this, a 3D U-Net was trained on an in-house datase...

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Detalles Bibliográficos
Autores principales: Meddeb, Aymen, Kossen, Tabea, Bressem, Keno K., Hamm, Bernd, Nagel, Sebastian N.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8704906/
https://www.ncbi.nlm.nih.gov/pubmed/34941650
http://dx.doi.org/10.3390/tomography7040078

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8704906/
https://www.ncbi.nlm.nih.gov/pubmed/34941650
http://dx.doi.org/10.3390/tomography7040078

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