MRI radiomics-based machine learning model integrated with clinic-radiological features for preoperative differentiation of sinonasal inverted papilloma and malignant sinonasal tumors

MRI radiomics-based machine learning model integrated with clinic-radiological features for preoperative differentiation of sinonasal inverted papilloma and malignant sinonasal tumors

ObjectiveTo explore the best MRI radiomics-based machine learning model for differentiation of sinonasal inverted papilloma (SNIP) and malignant sinonasal tumor (MST), and investigate whether the combination of radiomics features and clinic–radiological features can produce a superior diagnostic per...

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Bibliographic Details
Main Authors: Jinming Gu, Qiang Yu, Quanjiang Li, Juan Peng, Fajin Lv, Beibei Gong, Xiaodi Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-09-01
Series:Frontiers in Oncology
Subjects:
radiomics
machine learning
magnetic resonance imaging
sinonasal inverted papilloma
malignant sinonasal tumor
differential diagnosis
Online Access:https://www.frontiersin.org/articles/10.3389/fonc.2022.1003639/full

Internet

https://www.frontiersin.org/articles/10.3389/fonc.2022.1003639/full

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