Texture Analysis in Cerebral Gliomas: A Review of the Literature

Texture Analysis of Imaging: What Radiologists Need to Know

(2019) Bino A. Varghese et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

MRI texture analysis based on 3D tumor measurement reflects the IDH1 mutations in gliomas – A preliminary study

(2019) Liang Han et al.   EUROPEAN JOURNAL OF RADIOLOGY

Texture analysis on diffusion tensor imaging: discriminating glioblastoma from single brain metastasis

(2018) Karoline Skogen et al.   ACTA RADIOLOGICA

The effect of glioblastoma heterogeneity on survival stratification: a multimodal MR imaging texture analysis

(2018) Yang Liu et al.   ACTA RADIOLOGICA

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

Imaging Genetic Heterogeneity in Glioblastoma and Other Glial Tumors: Review of Current Methods and Future Directions

(2018) Daniel Chow et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Quantitative texture analysis in the prediction of IDH status in low-grade gliomas

(2018) Asgeir Store Jakola et al.   CLINICAL NEUROLOGY AND NEUROSURGERY

Primary central nervous system lymphoma and atypical glioblastoma: Differentiation using radiomics approach

(2018) Hie Bum Suh et al.   EUROPEAN RADIOLOGY

Genotype prediction of ATRX mutation in lower-grade gliomas using an MRI radiomics signature

(2018) Yiming Li et al.   EUROPEAN RADIOLOGY

Radiomics strategy for glioma grading using texture features from multiparametric MRI

(2018) Qiang Tian et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Molecular classification of patients with grade II/III glioma using quantitative MRI characteristics

(2018) Naeim Bahrami et al.   JOURNAL OF NEURO-ONCOLOGY

Cardiac Computed Tomography Radiomics

(2018) Márton Kolossváry et al.   JOURNAL OF THORACIC IMAGING

Evaluation of radiomic texture feature error due to MRI acquisition and reconstruction: A simulation study utilizing ground truth

(2018) Fei Yang et al.   Physica Medica-European Journal of Medical Physics

Machine Learning-based Texture Analysis of Contrast-enhanced MR Imaging to Differentiate between Glioblastoma and Primary Central Nervous System Lymphoma

(2018) Akira Kunimatsu et al.   Magnetic Resonance in Medical Sciences

Comparison between Glioblastoma and Primary Central Nervous System Lymphoma Using MR Image-based Texture Analysis

(2018) Akira Kunimatsu et al.   Magnetic Resonance in Medical Sciences

Novel Radiomic Features based on Joint Intensity Matrices for Predicting Glioblastoma Patient Survival Time

(2018) Ahmad Chaddad et al.   IEEE Journal of Biomedical and Health Informatics

MRI features predict p53 status in lower-grade gliomas via a machine-learning approach

(2018) Yiming Li et al.   NeuroImage-Clinical

Glioblastoma and primary central nervous system lymphoma: Preoperative differentiation by using MRI-based 3D texture analysis

(2018) Dong-Dong Xiao et al.   CLINICAL NEUROLOGY AND NEUROSURGERY

Quantitative Radiomics: Impact of Pulse Sequence Parameter Selection on MRI-Based Textural Features of the Brain

(2018) John Ford et al.   Contrast Media & Molecular Imaging

Shape Features of the Lesion Habitat to Differentiate Brain Tumor Progression from Pseudoprogression on Routine Multiparametric MRI: A Multisite Study

(2018) M. Ismail et al.   AMERICAN JOURNAL OF NEURORADIOLOGY

Quantitative variations in texture analysis features dependent on MRI scanning parameters: A phantom model

(2018) Karen Buch et al.   Journal of Applied Clinical Medical Physics

Histogram analysis of diffusion kurtosis imaging derived maps may distinguish between low and high grade gliomas before surgery

(2017) Xi-Xun Qi et al.   EUROPEAN RADIOLOGY

MRI features can predict EGFR expression in lower grade gliomas: A voxel-based radiomic analysis

(2017) Yiming Li et al.   EUROPEAN RADIOLOGY

Experimental Texture Analysis in Glioblastoma

(2017) Nicolin Hainc et al.   INVESTIGATIVE RADIOLOGY

Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading

(2017) Tian Xie et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

MR textural analysis on T2 FLAIR images for the prediction of true oligodendroglioma by the 2016 WHO genetic classification

(2017) Wenting Rui et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Differentiating enhancing multiple sclerosis lesions, glioblastoma, and lymphoma with dynamic texture parameters analysis (DTPA): A feasibility study

(2017) Rajeev Kumar Verma et al.   MEDICAL PHYSICS

Quantitative imaging biomarkers for risk stratification of patients with recurrent glioblastoma treated with bevacizumab

(2017) Patrick Grossmann et al.   NEURO-ONCOLOGY

CT Texture Analysis: Definitions, Applications, Biologic Correlates, and Challenges

(2017) Meghan G. Lubner et al.   RADIOGRAPHICS

MRI radiomics analysis of molecular alterations in low-grade gliomas

(2017) Ben Shofty et al.   International Journal of Computer Assisted Radiology and Surgery

Radiomic model for predicting mutations in the isocitrate dehydrogenase gene in glioblastomas

(2017) Kevin Li-Chun Hsieh et al.   Oncotarget

Mining textural knowledge in biological images: Applications, methods and trends

(2017) Santa Di Cataldo et al.   Computational and Structural Biotechnology Journal

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

(2017) David Molina et al.   PLoS One

Diffusion tensor image features predict IDH genotype in newly diagnosed WHO grade II/III gliomas

(2017) Paul Eichinger 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

Imaging Heterogeneity in Lung Cancer: Techniques, Applications, and Challenges

(2016) Usman Bashir et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

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

Errors, limitations, and pitfalls in the diagnosis of central and peripheral nervous system lesions in intraoperative cytology and frozen sections

(2016) Priyanka Chand et al.   Journal of Cytology

Extracted magnetic resonance texture features discriminate between phenotypes and are associated with overall survival in glioblastoma multiforme patients

(2016) Ahmad Chaddad et al.   MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING

Assessment of tissue heterogeneity using diffusion tensor and diffusion kurtosis imaging for grading gliomas

(2016) Rajikha Raja et al.   NEURORADIOLOGY

Introduction of High Throughput Magnetic Resonance T2-Weighted Image Texture Analysis for WHO Grade 2 and 3 Gliomas

(2016) Manabu Kinoshita et al.   PLoS One

Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models

(2016) Philipp Kickingereder et al.   RADIOLOGY

Texture Feature Ratios from Relative CBV Maps of Perfusion MRI Are Associated with Patient Survival in Glioblastoma

(2015) J. Lee et al.   AMERICAN JOURNAL OF NEURORADIOLOGY

A framework for multimodal imaging-based prognostic model building: Preliminary study on multimodal MRI in Glioblastoma Multiforme

(2015) T. Upadhaya et al.   IRBM

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

Prognostic role of IDH mutations in gliomas: a meta-analysis of 55 observational studies

(2015) Liang Xia et al.   Oncotarget

Radiogenomics: What It Is and Why It Is Important

(2015) Maciej A. Mazurowski   Journal of the American College of Radiology

Computer-extracted MR imaging features are associated with survival in glioblastoma patients

(2014) Maciej A. Mazurowski et al.   JOURNAL OF NEURO-ONCOLOGY

ADC texture-An imaging biomarker for high-grade glioma?

(2014) Patrik Brynolfsson et al.   MEDICAL PHYSICS

Glioma: Application of Whole-Tumor Texture Analysis of Diffusion-Weighted Imaging for the Evaluation of Tumor Heterogeneity

(2014) Young Jin Ryu et al.   PLoS One

Three-dimensional solid texture analysis in biomedical imaging: Review and opportunities

(2013) Adrien Depeursinge et al.   MEDICAL IMAGE ANALYSIS

Characterization of Microcirculation in Multiple Sclerosis Lesions by Dynamic Texture Parameter Analysis (DTPA)

(2013) Rajeev Kumar Verma et al.   PLoS One

MR Imaging Predictors of Molecular Profile and Survival: Multi-institutional Study of the TCGA Glioblastoma Data Set

(2013) David A. Gutman et al.   RADIOLOGY

CT texture analysis using the filtration-histogram method: what do the measurements mean?

(2013) Kenneth A. Miles et al.   CANCER IMAGING

The influence of field strength and different clinical breast MRI protocols on the outcome of texture analysis using foam phantoms

(2011) Shelley A. Waugh et al.   MEDICAL PHYSICS

Prognostic significance of IDH-1 and MGMT in patients with glioblastoma: One step forward, and one step back?

(2011) Stephanie E Combs et al.   Radiation Oncology

Gliomas: Histogram Analysis of Apparent Diffusion Coefficient Maps with Standard- or High-b-Value Diffusion-weighted MR Imaging—Correlation with Tumor Grade

(2011) Yusuhn Kang et al.   RADIOLOGY

A Novel Method for Analyzing DSCE-Images With an Application to Tumor Grading

(2010) Johannes Slotboom et al.   INVESTIGATIVE RADIOLOGY

Effects of Magnetic Resonance Image Interpolation on the Results of Texture-Based Pattern Classification

(2009) Marius E. Mayerhoefer et al.   INVESTIGATIVE RADIOLOGY

Effects of MRI acquisition parameter variations and protocol heterogeneity on the results of texture analysis and pattern discrimination: An application-oriented study

(2009) Marius E. Mayerhoefer et al.   MEDICAL PHYSICS