Machine learning for differentiation of lipid-poor adrenal adenoma and subclinical pheochromocytoma based on multiphase CT imaging radiomics

Machine learning for differentiation of lipid-poor adrenal adenoma and subclinical pheochromocytoma based on multiphase CT imaging radiomics

Abstract Background There is a paucity of research investigating the application of machine learning techniques for distinguishing between lipid-poor adrenal adenoma (LPA) and subclinical pheochromocytoma (sPHEO) based on radiomic features extracted from non-contrast and dynamic contrast-enhanced co...

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Bibliographic Details
Main Authors: Dao-xiong Xiao, Jian-ping Zhong, Ji-dong Peng, Cun-geng Fan, Xiao-chun Wang, Xing-lin Wen, Wei-wei Liao, Jun Wang, Xiao-feng Yin
Format: Article
Language:English
Published: BMC 2023-10-01
Series:BMC Medical Imaging
Subjects:
Computed tomography
Machine learning
Radiomics
Lipid-poor adrenal adenoma
Subclinical pheochromocytoma
Online Access:https://doi.org/10.1186/s12880-023-01106-2

Internet

https://doi.org/10.1186/s12880-023-01106-2

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