Radiomics-based machine learning models to distinguish between metastatic and healthy bone using lesion-center-based geometric regions of interest

Radiomics-based machine learning classifiers have shown potential for detecting bone metastases (BM) and for evaluating BM response to radiotherapy (RT). However, current radiomics models require large datasets of images with expert-segmented 3D regions of interest (ROIs). Full ROI segmentation is t...

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Detalles Bibliográficos
Autores principales: Naseri, Hossein, Skamene, Sonia, Tolba, Marwan, Faye, Mame Daro, Ramia, Paul, Khriguian, Julia, Patrick, Haley, Andrade Hernandez, Aixa X., David, Marc, Kildea, John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198102/
https://www.ncbi.nlm.nih.gov/pubmed/35701461
http://dx.doi.org/10.1038/s41598-022-13379-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9198102/
https://www.ncbi.nlm.nih.gov/pubmed/35701461
http://dx.doi.org/10.1038/s41598-022-13379-8

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