Deep learning-driven modality imputation and subregion segmentation to enhance high-grade glioma grading

Abstract Purpose This study aims to develop a deep learning framework that leverages modality imputation and subregion segmentation to improve grading accuracy in high-grade gliomas. Materials and methods A retrospective analysis was conducted using data from 1,251 patients in the BraTS2021 dataset...

Full description

Saved in:

Bibliographic Details
Main Authors:	Jiabin Yu, Qi Liu, Chenjie Xu, Qinli Zhou, Jiajun Xu, Lingying Zhu, Chen Chen, Yahan Zhou, Binggang Xiao, Lin Zheng, Xiaofeng Zhou, Fengming Zhang, Yuhang Ye, Hongmei Mi, Dongping Zhang, Li Yang, Zhiwei Wu, Jiayi Wang, Ming Chen, Zhirui Zhou, Haoyang Wang, Vicky Y. Wang, Enyu Wang, Dong Xu
Format:	Article
Language:	English
Published:	BMC 2025-05-01
Series:	BMC Medical Informatics and Decision Making
Subjects:	High-Grade glioma Modality imputation Subregion segmentation MRI Deep learning
Online Access:	https://doi.org/10.1186/s12911-025-03029-0
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!

Deep learning-driven modality imputation and subregion segmentation to enhance high-grade glioma grading

Similar Items