Cerebral Glioma Grading Using Bayesian Network with Features Extracted from Multiple Modalities of Magnetic Resonance Imaging-Reference-Cited by-同舟云学术

Cerebral Glioma Grading Using Bayesian Network with Features Extracted from Multiple Modalities of Magnetic Resonance Imaging

Published:2016-04-14 Issue:4 Volume:11 Page:e0153369
ISSN:1932-6203
Container-title:PLOS ONE
language:en
Short-container-title:PLoS ONE

Author:

Hu Jisu,Wu Wenbo,Zhu Bin,Wang Huiting,Liu Renyuan,Zhang Xin,Li Ming,Yang Yongbo,Yan Jing,Niu Fengnan,Tian Chuanshuai,Wang Kun,Yu Haiping,Chen Weibo,Wan Suiren,Sun Yu,Zhang Bing

Publisher

Public Library of Science (PLoS)

Subject

Multidisciplinary

Reference24 articles.

1. The 2007 WHO classification of tumours of the central nervous system;DN Louis;Acta Neuropathologica,2007

2. Glioma grading: Sensitivity, specificity, and predictive values of perfusion MR imaging and proton MR spectroscopic imaging compared with conventional MR imaging;M Law;American Journal of Neuroradiology,2003

3. High-grade and low-grade gliomas: differentiation by using perfusion MR imaging;B Hakyemez;Clinical Radiology,2005

4. Methodology of brain perfusion imaging;EL Barbier;Journal of Magnetic Resonance Imaging,2001

5. Principles of cerebral perfusion imaging by bolus tracking;L Ostergaard;Journal of Magnetic Resonance Imaging,2005

Cited by 3 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. The role of artificial intelligence in paediatric neuroradiology;Pediatric Radiology;2022-03-26

2. Machine Learning in Neuro-Oncology: Can Data Analysis From 5346 Patients Change Decision-Making Paradigms?;World Neurosurgery;2019-04

3. Arterial Spin-Labeling in Children with Brain Tumor: A Meta-Analysis;American Journal of Neuroradiology;2018-08-02