4.4 Review

Meningioma MRI radiomics and machine learning: systematic review, quality score assessment, and meta-analysis

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Radiology, Nuclear Medicine & Medical Imaging

Value of MRI Radiomics Based on Enhanced T1WI Images in Prediction of Meningiomas Grade

Hairui Chu et al.

Summary: The MRI radiomics method based on enhanced-T1WI images is effective in predicting the classification of meningiomas, providing valuable insights for clinical treatment planning.

ACADEMIC RADIOLOGY (2021)

Article Radiology, Nuclear Medicine & Medical Imaging

Differentiation Between Benign and Nonbenign Meningiomas by Using Texture Analysis From Multiparametric MRI

Chao Ke et al.

JOURNAL OF MAGNETIC RESONANCE IMAGING (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Radiomic Analysis of Craniopharyngioma and Meningioma in the Sellar/Parasellar Area with MR Images Features and Texture Features: A Feasible Study

Zerong Tian et al.

CONTRAST MEDIA & MOLECULAR IMAGING (2020)

Review Radiology, Nuclear Medicine & Medical Imaging

Radiomics of computed tomography and magnetic resonance imaging in renal cell carcinoma-a systematic review and meta-analysis

Stephan Ursprung et al.

EUROPEAN RADIOLOGY (2020)

Review Radiology, Nuclear Medicine & Medical Imaging

Prostate MRI radiomics: A systematic review and radiomic quality score assessment

Arnaldo Stanzione et al.

EUROPEAN JOURNAL OF RADIOLOGY (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis

Renato Cuocolo et al.

EUROPEAN RADIOLOGY (2020)

Review Oncology

Machine Learning in oncology: A clinical appraisal

Renato Cuocolo et al.

CANCER LETTERS (2020)

Article Instruments & Instrumentation

Automatic detection of the meningioma tumor firmness in MRI images

Atheer AlKubeyyer et al.

JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY (2020)

Article Radiology, Nuclear Medicine & Medical Imaging

Fully automated detection and segmentation of meningiomas using deep learning on routine multiparametric MRI

Kai Roman Laukamp et al.

EUROPEAN RADIOLOGY (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

A deep learning radiomics model for preoperative grading in meningioma

Yongbei Zhu et al.

EUROPEAN JOURNAL OF RADIOLOGY (2019)

Article Clinical Neurology

Radiomics approach for prediction of recurrence in skull base meningiomas

Yang Zhang et al.

NEURORADIOLOGY (2019)

Article Urology & Nephrology

Artificial Intellinence in Nephrology: Core Concepts, Clinical Applications, and Perspectives

Olivier Niel et al.

AMERICAN JOURNAL OF KIDNEY DISEASES (2019)

Article Mathematical & Computational Biology

Automatic Prediction of Meningioma Grade Image Based on Data Amplification and Improved Convolutional Neural Network

Hong Zhu et al.

COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE (2019)

Article Radiology, Nuclear Medicine & Medical Imaging

Comparison of machine learning classifiers for differentiation of grade 1 from higher gradings in meningioma: A multicenter radiomics study

Gordian Hamerla et al.

MAGNETIC RESONANCE IMAGING (2019)

Review Radiology, Nuclear Medicine & Medical Imaging

State of the Art: Machine Learning Applications in Glioma Imaging

Eyal Lotan et al.

AMERICAN JOURNAL OF ROENTGENOLOGY (2019)

Review Radiology, Nuclear Medicine & Medical Imaging

Exploring breast cancer response prediction to neoadjuvant systemic therapy using MRI-based radiomics: A systematic review

R. W. Y. Granzier et al.

EUROPEAN JOURNAL OF RADIOLOGY (2019)

Article Oncology

Imaging and diagnostic advances for intracranial meningiomas

Raymond Y. Huang et al.

NEURO-ONCOLOGY (2019)

Review Radiology, Nuclear Medicine & Medical Imaging

How to Perform a Systematic Review and Meta-analysis of Diagnostic Imaging Studies

Paul Cronin et al.

ACADEMIC RADIOLOGY (2018)

Review Clinical Neurology

Deep Learning in Neuroradiology

G. Zaharchuk et al.

AMERICAN JOURNAL OF NEURORADIOLOGY (2018)

Review Medicine, General & Internal

Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies The PRISMA-DTA Statement

Matthew D. F. McInnes et al.

JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2018)

Review Oncology

Tracking tumor biology with radiomics: A systematic review utilizing a radiomics quality score

Sebastian Sanduleanu et al.

RADIOTHERAPY AND ONCOLOGY (2018)

Review Oncology

An overview of meningiomas

Robin A. Buerki et al.

FUTURE ONCOLOGY (2018)

Article Health Care Sciences & Services

Mixture Model Segmentation System for Parasagittal Meningioma brain Tumor Classification based on Hybrid Feature Vector

L. Arokia Jesu Prabhu et al.

JOURNAL OF MEDICAL SYSTEMS (2018)

Review Oncology

Radiomics: the bridge between medical imaging and personalized medicine

Philippe Lambin et al.

NATURE REVIEWS CLINICAL ONCOLOGY (2017)

Article Clinical Neurology

Prognostic Factors of Atypical Meningioma : Overall Survival Rate and Progression Free Survival Rate

Jae Ho Lee et al.

JOURNAL OF KOREAN NEUROSURGICAL SOCIETY (2017)

Article Clinical Neurology

A national survey of the management of patients with incidental meningioma in the United Kingdom

Mujtaba H. Mohammad et al.

BRITISH JOURNAL OF NEUROSURGERY (2017)

Article Radiology, Nuclear Medicine & Medical Imaging

Radiomics: Images Are More than Pictures, They Are Data

Robert J. Gillies et al.

RADIOLOGY (2016)

Article Rehabilitation

A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research

Terry K. Koo et al.

JOURNAL OF CHIROPRACTIC MEDICINE (2016)

Article Clinical Neurology

Management of Petroclival Meningiomas: A Review of the Development of Current Therapy

Adrian J. Maurer et al.

JOURNAL OF NEUROLOGICAL SURGERY PART B-SKULL BASE (2014)

Article Medicine, General & Internal

QUADAS-2: A Revised Tool for the Quality Assessment of Diagnostic Accuracy Studies

Penny F. Whiting et al.

ANNALS OF INTERNAL MEDICINE (2011)

Article Public, Environmental & Occupational Health

Assessing the Performance of Prediction Models A Framework for Traditional and Novel Measures

Ewout W. Steyerberg et al.

EPIDEMIOLOGY (2010)

Article Cardiac & Cardiovascular Systems

Meta-analysis

Ton J. Cleophas et al.

CIRCULATION (2007)

Article Medicine, General & Internal

Measuring inconsistency in meta-analyses

JPT Higgins et al.

BMJ-BRITISH MEDICAL JOURNAL (2003)