Machine Learning Models Based on [<sup>18</sup>F]FDG PET Radiomics for Bone Marrow Assessment in Non-Hodgkin Lymphoma

Machine Learning Models Based on [<sup>18</sup>F]FDG PET Radiomics for Bone Marrow Assessment in Non-Hodgkin Lymphoma

Non-Hodgkin lymphoma is a heterogeneous group of cancers that triggers bone marrow infiltration in 20–40% of cases. Bone marrow biopsy in combination with a visual assessment of [<sup>18</sup>F]FDG PET/CT images is used to assess the marrow status. Despite the potential of both technique...

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Bibliographic Details
Main Authors: Eva Milara, Pilar Sarandeses, Ana Jiménez-Ubieto, Adriana Saviatto, Alexander P. Seiffert, F. J. Gárate, D. Moreno-Blanco, M. Poza, Enrique J. Gómez, Adolfo Gómez-Grande, Patricia Sánchez-González
Format: Article
Language:English
Published: MDPI AG 2024-11-01
Series:Applied Sciences
Subjects:
machine learning
radiomics
bone marrow involvement
Non-Hodgkin Lymphoma
segmentation
Online Access:https://www.mdpi.com/2076-3417/14/22/10291
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