Dual-Level Augmentation Radiomics Analysis for Multisequence MRI Meningioma Grading

Dual-Level Augmentation Radiomics Analysis for Multisequence MRI Meningioma Grading

Background: Preoperative, noninvasive prediction of meningioma grade is important for therapeutic planning and decision making. In this study, we propose a dual-level augmentation strategy incorporating image-level augmentation (IA) and feature-level augmentation (FA) to tackle class imbalance and i...

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Bibliographic Details
Main Authors: Zongyou Cai, Lun M. Wong, Ye Heng Wong, Hok-lam Lee, Kam-yau Li, Tiffany Y. So
Format: Article
Language:English
Published: MDPI AG 2023-11-01
Series:Cancers
Subjects:
radiomics
meningioma
magnetic resonance imaging
data augmentation
machine learning
Online Access:https://www.mdpi.com/2072-6694/15/22/5459

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