Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models.
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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.Prediction of malignancy by a radiomic signature from contrast agent-free diffusion MRI in suspicious breast lesions found on screening mammography.An Update on the Approach to the Imaging of Brain Tumors.Quantitative Imaging Biomarkers for Risk Stratification of Patients with Recurrent Glioblastoma Treated with Bevacizumab.Magnetic Resonance Imaging-Based Radiomic Profiles Predict Patient Prognosis in Newly Diagnosed Glioblastoma Before TherapyA comparative study of machine learning methods for time-to-event survival data for radiomics risk modelling.MRI Texture Analysis Reflects Histopathology Parameters in Thyroid Cancer - A First Preliminary Study.A Fully-Automatic Multiparametric Radiomics Model: Towards Reproducible and Prognostic Imaging Signature for Prediction of Overall Survival in Glioblastoma Multiforme.Radiogenomic analysis of hypoxia pathway is predictive of overall survival in Glioblastoma.MR textural analysis on T2 FLAIR images for the prediction of true oligodendroglioma by the 2016 WHO genetic classification.A predictive model for distinguishing radiation necrosis from tumour progression after gamma knife radiosurgery based on radiomic features from MR images.Radiomics signature: A potential biomarker for the prediction of MGMT promoter methylation in glioblastoma.Diffusion radiomics as a diagnostic model for atypical manifestation of primary central nervous system lymphoma: development and multicenter external validation.Radiomic subtyping improves disease stratification beyond key molecular, clinical and standard imaging characteristics in patients with glioblastoma.Radiomics as a Quantitative Imaging Biomarker: Practical Considerations and the Current Standpoint in Neuro-oncologic Studies.MRI features can predict EGFR expression in lower grade gliomas: A voxel-based radiomic analysis.Exploring Applications of Radiomics in Magnetic Resonance Imaging of Head and Neck Cancer: A Systematic Review.Imaging in neuro-oncology.Radiomic MRI signature reveals three distinct subtypes of glioblastoma with different clinical and molecular characteristics, offering prognostic value beyond IDH1.A radiomic signature as a non-invasive predictor of progression-free survival in patients with lower-grade gliomasCombined FET PET/MRI radiomics differentiates radiation injury from recurrent brain metastasisMolecular profiles of tumor contrast enhancement: A radiogenomic analysis in anaplastic gliomasIdentifying the morphologic basis for radiomic features in distinguishing different Gleason grades of prostate cancer on MRI: Preliminary findingsLesion location implemented magnetic resonance imaging radiomics for predicting IDH and TERT promoter mutations in grade II/III gliomas
P2860
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P2860
Radiomic Profiling of Glioblastoma: Identifying an Imaging Predictor of Patient Survival with Improved Performance over Established Clinical and Radiologic Risk Models.
description
2016 nî lūn-bûn
@nan
2016年の論文
@ja
2016年論文
@yue
2016年論文
@zh-hant
2016年論文
@zh-hk
2016年論文
@zh-mo
2016年論文
@zh-tw
2016年论文
@wuu
2016年论文
@zh
2016年论文
@zh-cn
name
Radiomic Profiling of Glioblas ...... al and Radiologic Risk Models.
@en
Radiomic Profiling of Glioblas ...... al and Radiologic Risk Models.
@nl
type
label
Radiomic Profiling of Glioblas ...... al and Radiologic Risk Models.
@en
Radiomic Profiling of Glioblas ...... al and Radiologic Risk Models.
@nl
prefLabel
Radiomic Profiling of Glioblas ...... al and Radiologic Risk Models.
@en
Radiomic Profiling of Glioblas ...... al and Radiologic Risk Models.
@nl
P2093
P50
P1433
P1476
Radiomic Profiling of Glioblas ...... al and Radiologic Risk Models.
@en
P2093
Antje Wick
David Bonekamp
Heinz-Peter Schlemmer
Klaus H Maier-Hein
Michael Götz
Oliver Eidel
P304
P356
10.1148/RADIOL.2016160845
P407
P577
2016-06-20T00:00:00Z