A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions-Reference-Cited by-同舟云学术

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A deep learning radiomics analysis for identifying sinus invasion in patients with meningioma before operation using tumor and peritumoral regions

Published:2022-04 Issue: Volume:149 Page:110187
ISSN:0720-048X
Container-title:European Journal of Radiology
language:en
Short-container-title:European Journal of Radiology

Author:

Sun Kai,Zhang Jing,Liu Zhenyu,Qiu Qi,Gao Han,Liu Panpan,Chen Kuntao,Wei Wei,Wang Liang,Zhang Junting,Zhou Junlin,Tian Jie

Funder

Guizhou Provincial Health Commission

National Natural Science Foundation of China

Chinese Academy of Sciences Youth Innovation Promotion Association

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Reference26 articles.

1. 2007 World Health Organization classification of tumours of the central nervous system;Thurnher;Cancer Imaging,2009

2. Meningiomas: knowledge base, treatment outcomes, and uncertainties A RANO review;Rogers;J. Neurosurg.,2015

3. Feasibility of High-Resolution 3-Dimensional Sampling Perfection with Application-Optimized Contrast Using Different Flip Angle Evolution Imaging for the Preoperative Detection of Parasinus Meningioma: A Pilot Study Compared with Contrast-Enhanced Magnetic Resonance Venography

4. Perioperative and long-term outcomes from the management of parasagittal meningiomas invading the superior sagittal sinus;Raza;Neurosurgery.,2010

5. Venous preservation-guided resection: a changing paradigm in parasagittal meningioma surgery;Tomasello;J. Neurosurg.,2013

Cited by 10 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. Machine Learning on MRI Radiomic Features to Assess Recurrence Risk in High-grade Meningiomas;2024-08-14

2. Intracranial meningioma: A review of recent and emerging data on the utility of preoperative imaging for management;Journal of Neuroimaging;2024-08-07

3. Research Progress of Artificial Intelligence in the Grading and Classification of Meningiomas;Academic Radiology;2024-08

4. Progression/Recurrence of Meningioma: An Imaging Review Based on Magnetic Resonance Imaging;World Neurosurgery;2024-06

5. Predicting meningioma grades and pathologic marker expression via deep learning;European Radiology;2023-10-19

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