Development of a hybrid 2.5D deep learning model for glioma survival prediction using T1-weighted MRI from the CGGA database
Open Access
- 26 October 2025
- journal article
- Published by Elsevier in European Journal of Radiology Open
- Vol. 15, 100697
Abstract
No abstract availableKeywords
Funding Information
- Medical Science and Technology Project of Zhejiang Province (2022KY679)
- Medical Science and Technology Project of Zhejiang Province (2022RC116)
- Medical Science and Technology Project of Zhejiang Province (2024KY805)
- Natural Science Foundation of Zhejiang Province (LY22H160043)
- Natural Science Foundation of Zhejiang Province (LY21H160007)
This publication has 23 references indexed in Scilit:
- Automated Data Processing Workflows for Non‐Expert Users of NMR FacilitiesMagnetic Resonance in Chemistry, 2025
- A flexible 2.5D medical image segmentation approach with in-slice and cross-slice attentionComputers in Biology and Medicine, 2024
- Liquid Biopsies: Emerging role and clinical applications in solid tumoursTranslational Oncology, 2023
- Lung cancer survival period prediction and understanding: Deep learning approachesInternational Journal of Medical Informatics, 2021
- Chinese Glioma Genome Atlas (CGGA): A Comprehensive Resource with Functional Genomic Data from Chinese Glioma PatientsGenomics, Proteomics & Bioinformatics, 2021
- Toward reliable automatic liver and tumor segmentation using convolutional neural network based on 2.5D modelsInternational Journal of Computer Assisted Radiology and Surgery, 2020
- Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomasJournal of Neuro-Oncology, 2019
- Segmentation of tongue muscles from super-resolution magnetic resonance imagesMedical Image Analysis, 2015
- Molecular genetics of adult grade II gliomas: towards a comprehensive tumor classification systemJournal of Neuro-Oncology, 2012
- Clinical relevance of diffusion and perfusion magnetic resonance imaging in assessing intra-axial brain tumorsNeuroradiology, 2006