A Bayesian 2D functional linear model for gray-level co-occurrence matrices in texture analysis of lower grade gliomas

A Bayesian 2D functional linear model for gray-level co-occurrence matrices in texture analysis of lower grade gliomas

In cancer radiomics, textural features evaluated from image intensity-derived gray-level co-occurrence matrices (GLCMs) have been studied to evaluate gray-level spatial dependence within the regions of interest in the brain. Most of these analysis work with summary statistics (or texture-based featu...

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Bibliographic Details
Main Authors: Thierry Chekouo, Shariq Mohammed, Arvind Rao
Format: Article
Language:English
Published: Elsevier 2020-01-01
Series:NeuroImage: Clinical
Subjects:
Bayesian variable selection
2D functional data
GLCM
Imaging sequences
Lower grade glioma
Texture analysis
Online Access:http://www.sciencedirect.com/science/article/pii/S2213158220302746

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http://www.sciencedirect.com/science/article/pii/S2213158220302746

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