Multi-Level Feature Exploration and Fusion Network for Prediction of IDH Status in Gliomas From MRI-Reference-Cited by-同舟云学术

Multi-Level Feature Exploration and Fusion Network for Prediction of IDH Status in Gliomas From MRI

Published:2024-01 Issue:1 Volume:28 Page:42-53
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Zhang Jiawei¹^ORCID,Cao Jianyun²^ORCID,Tang Fan³,Xie Tao²^ORCID,Feng Qianjin¹,Huang Meiyan¹^ORCID

Affiliation:

1. School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing, Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China

2. Zhujiang Hospital, Southern Medical University, Guangzhou, China

3. Nanfang Hospital, Southern Medical University, Guangzhou, China

Funder

National Natural Science Foundation of China

Basic and Applied Basic Research Foundation of Guangdong Province

Science and Technology Planning Project of Guangzhou

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/10380963/10138367.pdf?arnumber=10138367

Reference50 articles.

1. CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2007-2011

2. The 2021 WHO Classification of Tumors of the Central Nervous System: a summary

3. IDH mutations predict longer survival and response to temozolomide in secondary glioblastoma

4. IDH1/2 mutation is a prognostic marker for survival and predicts response to chemotherapy for grade II gliomas concomitantly treated with radiation therapy

5. Magnetic resonance imaging-guided stereotactic biopsy: A review of 83 cases with outcomes

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Biologically interpretable multi-task deep learning pipeline predicts molecular alterations, grade, and prognosis in glioma patients;2024-02-20

2. Guest Editorial Computational Mathematics Modeling in Cancer Analysis;IEEE Journal of Biomedical and Health Informatics;2024-01

3. Real-Time Tracking and Inpainting Network with Joint Learning Iterative Modules for Ar-Based Dalk Surgical Navigation;2024

4. Quantitative analysis using intraoperative contrast-enhanced ultrasound in adult-type diffuse gliomas with isocitrate dehydrogenase mutations: association between hemodynamics and molecular features;Ultrasonography;2023-10-01