Radiomics in gliomas: clinical implications of computational modeling and fractal-based analysis
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Title
Radiomics in gliomas: clinical implications of computational modeling and fractal-based analysis
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Keywords
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Journal
NEURORADIOLOGY
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2020-04-06
DOI
10.1007/s00234-020-02403-1
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Note: Only part of the references are listed.- Optimizing Texture Retrieving Model for Multimodal MR Image-Based Support Vector Machine for Classifying Glioma
- (2019) Yang Yang et al. JOURNAL OF MAGNETIC RESONANCE IMAGING
- A Multi-parametric MRI-Based Radiomics Signature and a Practical ML Model for Stratifying Glioblastoma Patients Based on Survival Toward Precision Oncology
- (2019) Alexander F. I. Osman Frontiers in Computational Neuroscience
- Automatic glioma segmentation based on adaptive superpixel
- (2019) Yaping Wu et al. BMC MEDICAL IMAGING
- Computational quantitative MR image features - a potential useful tool in differentiating glioblastoma from solitary brain metastasis
- (2019) Katarina Petrujkić et al. EUROPEAN JOURNAL OF RADIOLOGY
- Edge Contrast of the FLAIR Hyperintense Region Predicts Survival in Patients with High-Grade Gliomas following Treatment with Bevacizumab
- (2018) N. Bahrami et al. AMERICAN JOURNAL OF NEURORADIOLOGY
- Molecular classification of patients with grade II/III glioma using quantitative MRI characteristics
- (2018) Naeim Bahrami et al. JOURNAL OF NEURO-ONCOLOGY
- Prediction of survival with multi-scale radiomic analysis in glioblastoma patients
- (2018) Ahmad Chaddad et al. MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
- Texture analysis- and support vector machine-assisted diffusional kurtosis imaging may allow in vivo gliomas grading and IDH-mutation status prediction: a preliminary study
- (2018) Sotirios Bisdas et al. Scientific Reports
- Deep convolutional neural networks for brain image analysis on magnetic resonance imaging: a review
- (2018) Jose Bernal et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
- Diagnostic accuracy of MRI texture analysis for grading gliomas
- (2018) Austin Ditmer et al. JOURNAL OF NEURO-ONCOLOGY
- Radiomic MRI Phenotyping of Glioblastoma: Improving Survival Prediction
- (2018) Sohi Bae et al. RADIOLOGY
- Overall survival prediction in glioblastoma multiforme patients from volumetric, shape and texture features using machine learning
- (2018) Parita Sanghani et al. SURGICAL ONCOLOGY-OXFORD
- Algorithmic three-dimensional analysis of tumor shape in MRI improves prognosis of survival in glioblastoma: a multi-institutional study
- (2017) Nicholas Czarnek et al. JOURNAL OF NEURO-ONCOLOGY
- Imaging correlates for the 2016 update on WHO classification of grade II/III gliomas: implications for IDH, 1p/19q and ATRX status
- (2017) Rachel L. Delfanti et al. JOURNAL OF NEURO-ONCOLOGY
- Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation
- (2017) Konstantinos Kamnitsas et al. MEDICAL IMAGE ANALYSIS
- Brain tumor segmentation with Deep Neural Networks
- (2017) Mohammad Havaei et al. MEDICAL IMAGE ANALYSIS
- Fractal and Gray Level Cooccurrence Matrix Computational Analysis of Primary Osteosarcoma Magnetic Resonance Images Predicts the Chemotherapy Response
- (2017) Goran J. Djuričić et al. Frontiers in Oncology
- A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme
- (2017) Jiangwei Lao et al. Scientific Reports
- A Fully-Automatic Multiparametric Radiomics Model: Towards Reproducible and Prognostic Imaging Signature for Prediction of Overall Survival in Glioblastoma Multiforme
- (2017) Qihua 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
- Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival
- (2016) David Molina et al. BRITISH JOURNAL OF RADIOLOGY
- Diagnostic performance of texture analysis on MRI in grading cerebral gliomas
- (2016) Karoline Skogen et al. EUROPEAN JOURNAL OF RADIOLOGY
- Radiomic features from the peritumoral brain parenchyma on treatment-naïve multi-parametric MR imaging predict long versus short-term survival in glioblastoma multiforme: Preliminary findings
- (2016) Prateek Prasanna et al. EUROPEAN RADIOLOGY
- Identifying spatial imaging biomarkers of glioblastoma multiforme for survival group prediction
- (2016) Mu Zhou et al. JOURNAL OF MAGNETIC RESONANCE IMAGING
- Radiomics in Brain Tumors
- (2016) Aikaterini Kotrotsou et al. Magnetic Resonance Imaging Clinics of North America
- Applications of Deep Learning in Biomedicine
- (2016) Polina Mamoshina et al. MOLECULAR PHARMACEUTICS
- Multimodal imaging patterns predict survival in recurrent glioblastoma patients treated with bevacizumab
- (2016) Ken Chang et al. NEURO-ONCOLOGY
- Radiomics: Images Are More than Pictures, They Are Data
- (2016) Robert J. Gillies et al. RADIOLOGY
- Evaluation of tumor-derived MRI-texture features for discrimination of molecular subtypes and prediction of 12-month survival status in glioblastoma
- (2015) Dalu Yang et al. MEDICAL PHYSICS
- Imaging patterns predict patient survival and molecular subtype in glioblastoma via machine learning techniques
- (2015) Luke Macyszyn et al. NEURO-ONCOLOGY
- Deep convolutional neural networks for multi-modality isointense infant brain image segmentation
- (2015) Wenlu Zhang et al. NEUROIMAGE
- Glioma Groups Based on 1p/19q, IDH, and TERT Promoter Mutations in Tumors
- (2015) Jeanette E. Eckel-Passow et al. NEW ENGLAND JOURNAL OF MEDICINE
- Fractal analysis: fractal dimension and lacunarity from MR images for differentiating the grades of glioma
- (2015) K A Smitha et al. PHYSICS IN MEDICINE AND BIOLOGY
- Big Data In Health Care: Using Analytics To Identify And Manage High-Risk And High-Cost Patients
- (2014) David W. Bates et al. HEALTH AFFAIRS
- Glioblastoma Multiforme: Exploratory Radiogenomic Analysis by Using Quantitative Image Features
- (2014) Olivier Gevaert et al. RADIOLOGY
- Quantitative Imaging Network: Data Sharing and Competitive AlgorithmValidation Leveraging The Cancer Imaging Archive
- (2014) Jayashree Kalpathy-Cramer et al. Translational Oncology
- Radiologically Defined Ecological Dynamics and Clinical Outcomes in Glioblastoma Multiforme: Preliminary Results
- (2014) Mu Zhou et al. Translational Oncology
- Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach
- (2014) Hugo J. W. L. Aerts et al. Nature Communications
- Glioblastoma Multiforme: A Look Inside Its Heterogeneous Nature
- (2014) Maria-del-Mar Inda et al. Cancers
- Evaluating RadLex and Real World Radiology Reporting
- (2013) Marta E. Heilbrun ACADEMIC RADIOLOGY
- Fractal analysis in radiological and nuclear medicine perfusion imaging: a systematic review
- (2013) Florian Michallek et al. EUROPEAN RADIOLOGY
- State of the art survey on MRI brain tumor segmentation
- (2013) Nelly Gordillo et al. MAGNETIC RESONANCE IMAGING
- Fractals in the Neurosciences, Part II
- (2013) Antonio Di Ieva et al. NEUROSCIENTIST
- Fractals in the Neurosciences, Part I: General Principles and Basic Neurosciences
- (2013) A. Di Ieva et al. NEUROSCIENTIST
- Intratumor heterogeneity in human glioblastoma reflects cancer evolutionary dynamics
- (2013) A. Sottoriva et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Differentiation of True Progression from Pseudoprogression in Glioblastoma Treated with Radiation Therapy and Concomitant Temozolomide: Comparison Study of Standard and High-b-Value Diffusion-weighted Imaging
- (2013) Hee Ho Chu et al. RADIOLOGY
- MR Imaging Predictors of Molecular Profile and Survival: Multi-institutional Study of the TCGA Glioblastoma Data Set
- (2013) David A. Gutman et al. RADIOLOGY
- Quantitative Imaging in Cancer Evolution and Ecology
- (2013) Robert A. Gatenby et al. RADIOLOGY
- Hotspot Mutations in H3F3A and IDH1 Define Distinct Epigenetic and Biological Subgroups of Glioblastoma
- (2012) Dominik Sturm et al. CANCER CELL
- Radiomics: Extracting more information from medical images using advanced feature analysis
- (2012) Philippe Lambin et al. EUROPEAN JOURNAL OF CANCER
- Radiomics: the process and the challenges
- (2012) Virendra Kumar et al. MAGNETIC RESONANCE IMAGING
- Three-dimensional susceptibility-weighted imaging at 7 T using fractal-based quantitative analysis to grade gliomas
- (2012) Antonio Di Ieva et al. NEURORADIOLOGY
- Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing
- (2012) Marco Gerlinger et al. NEW ENGLAND JOURNAL OF MEDICINE
- Non–Small Cell Lung Cancer: Identifying Prognostic Imaging Biomarkers by Leveraging Public Gene Expression Microarray Data—Methods and Preliminary Results
- (2012) Olivier Gevaert et al. RADIOLOGY
- Computer-assisted and fractal-based morphometric assessment of microvascularity in histological specimens of gliomas
- (2012) Antonio Di Ieva et al. Scientific Reports
- Pseudoprogression and Pseudoresponse: Imaging Challenges in the Assessment of Posttreatment Glioma
- (2011) L.C. Hygino da Cruz et al. AMERICAN JOURNAL OF NEURORADIOLOGY
- Quantitative volumetric analysis of conventional MRI response in recurrent glioblastoma treated with bevacizumab
- (2011) B. M. Ellingson et al. NEURO-ONCOLOGY
- Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme
- (2011) Pascal O. Zinn et al. PLoS One
- Fractal Analysis of the Susceptibility Weighted Imaging Patterns in Malignant Brain Tumors During Antiangiogenic Treatment: Technical Report on Four Cases Serially Imaged by 7 T Magnetic Resonance During a Period of Four Weeks
- (2011) Antonio Di Ieva et al. World Neurosurgery
- Identification of a CpG Island Methylator Phenotype that Defines a Distinct Subgroup of Glioma
- (2010) Houtan Noushmehr et al. CANCER CELL
- Angioarchitectural morphometrics of brain tumors: Are there any potential histopathological biomarkers?
- (2010) Antonio Di Ieva MICROVASCULAR RESEARCH
- Correlation of microvascular fractal dimension with positron emission tomography [11C]-methionine uptake in glioblastoma multiforme: Preliminary findings
- (2010) Antonio Di Ieva et al. MICROVASCULAR RESEARCH
- Peritumoral edema on MRI at initial diagnosis: an independent prognostic factor for glioblastoma?
- (2009) K. Schoenegger et al. EUROPEAN JOURNAL OF NEUROLOGY
- A Network Model of a Cooperative Genetic Landscape in Brain Tumors
- (2009) Markus Bredel et al. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- Isocitrate Dehydrogenase 1 Codon 132 Mutation Is an Important Prognostic Biomarker in Gliomas
- (2009) Marc Sanson et al. JOURNAL OF CLINICAL ONCOLOGY
- Computer-aided detection of metastatic brain tumors using automated three-dimensional template matching
- (2009) Robert D. Ambrosini et al. JOURNAL OF MAGNETIC RESONANCE IMAGING
- IDH1andIDH2Mutations in Gliomas
- (2009) Hai Yan et al. NEW ENGLAND JOURNAL OF MEDICINE
- Fractal-based brain tumor detection in multimodal MRI
- (2008) Khan M. Iftekharuddin et al. APPLIED MATHEMATICS AND COMPUTATION
- A new segmentation system for brain MR images based on fuzzy techniques
- (2008) S.R. Kannan APPLIED SOFT COMPUTING
- Correlation of O6-Methylguanine Methyltransferase (MGMT) Promoter Methylation With Clinical Outcomes in Glioblastoma and Clinical Strategies to Modulate MGMT Activity
- (2008) Monika E. Hegi et al. JOURNAL OF CLINICAL ONCOLOGY
- Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods
- (2008) Pantelis Georgiadis et al. MAGNETIC RESONANCE IMAGING
- Comprehensive genomic characterization defines human glioblastoma genes and core pathways
- (2008) Roger McLendon et al. NATURE
- Identification of intratumour low frequency microvascular components via BOLD signal fractal dimension mapping
- (2008) Graeme Wardlaw et al. Physica Medica-European Journal of Medical Physics
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