Deep learning-based tumor segmentation and radiogenomic model for predicting EGFR amplification and assessing intratumoural heterogeneity in glioblastoma

Deep learning-based tumor segmentation and radiogenomic model for predicting EGFR amplification and assessing intratumoural heterogeneity in glioblastoma

Abstract Objectives To predict epidermal growth factor receptor (EGFR) amplification and explore the intratumoural heterogeneity of glioblastoma (GBM) using deep learning segmentation-based radiogenomics. Methods A total of 654 patients were included from multiple datasets, divided into a training c...

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Bibliographic Details
Main Authors: Jianpeng Liu, Chuyun Shen, Shufan Jiang, Yanfei Wu, Jiaqi Tu, Yifang Bao, Haiqing Li, Na Wang, Ying Liu, Ji Xiong, Xueling Liu, Yuxin Li
Format: Article
Language:English
Published: SpringerOpen 2025-07-01
Series:Journal of Big Data
Subjects:
Glioblastoma
Epidermal growth factor receptor
Deep learning
Machine learning
Radiogenomics
Online Access:https://doi.org/10.1186/s40537-025-01221-7
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https://doi.org/10.1186/s40537-025-01221-7

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