Optimizing Neuro-Oncology Imaging: A Review of Deep Learning Approaches for Glioma Imaging
出版年份 2019 全文链接
标题
Optimizing Neuro-Oncology Imaging: A Review of Deep Learning Approaches for Glioma Imaging
作者
关键词
-
出版物
Cancers
Volume 11, Issue 6, Pages 829
出版商
MDPI AG
发表日期
2019-06-14
DOI
10.3390/cancers11060829
参考文献
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。- Machine Learning in Neuro-Oncology: Can Data Analysis From 5346 Patients Change Decision-Making Paradigms?
- (2019) Christopher A. Sarkiss et al. World Neurosurgery
- Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas
- (2018) P. Chang et al. AMERICAN JOURNAL OF NEURORADIOLOGY
- Current Applications and Future Impact of Machine Learning in Radiology
- (2018) Garry Choy et al. RADIOLOGY
- From hype to reality: data science enabling personalized medicine
- (2018) Holger Fröhlich et al. BMC Medicine
- Prediction of Pseudoprogression versus Progression using Machine Learning Algorithm in Glioblastoma
- (2018) Bum-Sup Jang et al. Scientific Reports
- Multimodal 3D DenseNet for IDH Genotype Prediction in Gliomas
- (2018) Sen Liang et al. Genes
- Residual Deep Convolutional Neural Network Predicts MGMT Methylation Status
- (2017) Panagiotis Korfiatis et al. JOURNAL OF DIGITAL IMAGING
- Brain tumor segmentation with Deep Neural Networks
- (2017) Mohammad Havaei et al. MEDICAL IMAGE ANALYSIS
- Radiomics: the bridge between medical imaging and personalized medicine
- (2017) Philippe Lambin et al. Nature Reviews Clinical Oncology
- Incidence of Tumour Progression and Pseudoprogression in High-Grade Gliomas: a Systematic Review and Meta-Analysis
- (2017) Abdul W. Abbasi et al. Clinical Neuroradiology
- Optimizing a machine learning based glioma grading system using multi-parametric MRI histogram and texture features
- (2017) Xin Zhang et al. Oncotarget
- Deep Learning based Radiomics (DLR) and its usage in noninvasive IDH1 prediction for low grade glioma
- (2017) Zeju Li et al. Scientific Reports
- The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary
- (2016) David N. Louis et al. ACTA NEUROPATHOLOGICA
- Noninvasive IDH1 mutation estimation based on a quantitative radiomics approach for grade II glioma
- (2016) Jinhua Yu et al. EUROPEAN RADIOLOGY
- Stratification of pseudoprogression and true progression of glioblastoma multiform based on longitudinal diffusion tensor imaging without segmentation
- (2016) Xiaohua Qian et al. MEDICAL PHYSICS
- Radiogenomics to characterize regional genetic heterogeneity in glioblastoma
- (2016) Leland S. Hu et al. NEURO-ONCOLOGY
- Radiomics: Images Are More than Pictures, They Are Data
- (2016) Robert J. Gillies et al. RADIOLOGY
- Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma
- (2016) Sied Kebir et al. Oncotarget
- The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
- (2015) Bjoern H. Menze et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques
- (2015) Luke Macyszyn et al. NEURO-ONCOLOGY
- CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2008-2012
- (2015) Quinn T. Ostrom et al. NEURO-ONCOLOGY
- A Generic Support Vector Machine Model for Preoperative Glioma Survival Associations
- (2015) Kyrre E. Emblem et al. RADIOLOGY
- Semi-automated segmentation of pre-operative low grade gliomas in magnetic resonance imaging
- (2015) Zeynettin Akkus et al. CANCER IMAGING
- Fully automatic GBM segmentation in the TCGA-GBM dataset: Prognosis and correlation with VASARI features
- (2015) Emmanuel Rios Velazquez et al. Scientific Reports
- A novel, reproducible, and objective method for volumetric magnetic resonance imaging assessment of enhancing glioblastoma
- (2014) Charles W. Kanaly et al. JOURNAL OF NEUROSURGERY
- Evaluation of pseudoprogression in patients with glioblastoma multiforme using dynamic magnetic resonance imaging with ferumoxytol calls RANO criteria into question
- (2014) M. Nasseri et al. NEURO-ONCOLOGY
- Glioblastoma Multiforme: Exploratory Radiogenomic Analysis by Using Quantitative Image Features
- (2014) Olivier Gevaert et al. RADIOLOGY
- Semiautomated Volumetric Measurement on Postcontrast MR Imaging for Analysis of Recurrent and Residual Disease in Glioblastoma Multiforme
- (2013) D.S. Chow et al. AMERICAN JOURNAL OF NEURORADIOLOGY
- Imaging descriptors improve the predictive power of survival models for glioblastoma patients
- (2013) M. A. Mazurowski et al. NEURO-ONCOLOGY
- MR Imaging Predictors of Molecular Profile and Survival: Multi-institutional Study of the TCGA Glioblastoma Data Set
- (2013) David A. Gutman et al. RADIOLOGY
- Key concepts in glioblastoma therapy
- (2012) Jiri Bartek et al. JOURNAL OF NEUROLOGY NEUROSURGERY AND PSYCHIATRY
- Radiomics: the process and the challenges
- (2012) Virendra Kumar et al. MAGNETIC RESONANCE IMAGING
- Pseudoprogression and Pseudoresponse: Imaging Challenges in the Assessment of Posttreatment Glioma
- (2011) L.C. Hygino da Cruz et al. AMERICAN JOURNAL OF NEURORADIOLOGY
- Support vector machine multiparametric MRI identification of pseudoprogression from tumor recurrence in patients with resected glioblastoma
- (2011) Xintao Hu et al. JOURNAL OF MAGNETIC RESONANCE IMAGING
- Clinical trial end points for high-grade glioma: the evolving landscape
- (2011) D. A. Reardon et al. NEURO-ONCOLOGY
- Genetics of Glioblastoma: A Window into Its Imaging and Histopathologic Variability
- (2011) Clifford J. Belden et al. RADIOGRAPHICS
- Computer-aided Diagnosis: How to Move from the Laboratory to the Clinic
- (2011) Bram van Ginneken et al. RADIOLOGY
- Texture Analysis: A Review of Neurologic MR Imaging Applications
- (2010) A. Kassner et al. AMERICAN JOURNAL OF NEURORADIOLOGY
- Updated Response Assessment Criteria for High-Grade Gliomas: Response Assessment in Neuro-Oncology Working Group
- (2010) Patrick Y. Wen et al. JOURNAL OF CLINICAL ONCOLOGY
- IDH1 Mutations as Molecular Signature and Predictive Factor of Secondary Glioblastomas
- (2009) S. Nobusawa et al. CLINICAL CANCER RESEARCH
- Classification of brain tumor type and grade using MRI texture and shape in a machine learning scheme
- (2009) Evangelia I. Zacharaki et al. MAGNETIC RESONANCE IN MEDICINE
- IDH1andIDH2Mutations in Gliomas
- (2009) Hai Yan et al. NEW ENGLAND JOURNAL OF MEDICINE
- Brain Tumor Imaging in Clinical Trials
- (2008) J.W. Henson et al. AMERICAN JOURNAL OF NEURORADIOLOGY
- Clinical features, mechanisms, and management of pseudoprogression in malignant gliomas
- (2008) Dieta Brandsma et al. LANCET ONCOLOGY
- Comprehensive genomic characterization defines human glioblastoma genes and core pathways
- (2008) Roger McLendon et al. NATURE
- Response criteria for glioma
- (2008) A Gregory Sorensen et al. Nature clinical practice. Oncology
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started