Multi-model radiomics and machine learning for differentiating lipid-poor adrenal adenomas from metastases using automatic segmentation

Multi-model radiomics and machine learning for differentiating lipid-poor adrenal adenomas from metastases using automatic segmentation

BackgroundRadiomics based on automatic segmentation of CT images has emerged as a highly promising approach for differentiating adrenal adenomas from metastases in clinical practice; however, its preoperative diagnostic value has not been fully evaluated in previously developed methodologies.Objecti...

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Bibliographic Details
Main Authors: Shengnan Yin, Ning Ding, Shaocai Wang, Mengjuan Li, Yichi Zhang, Jiacheng Shen, Haitao Hu, Yiding Ji, Long Jin
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Oncology
Subjects:
adrenal masses
radiomics
contrast-enhanced CT
machine learning
SHAP analysis
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2025.1619341/full
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