Spatial Shrinkage Estimation of Diffusion Tensors on Diffusion-Weighted Imaging Data

DOI10.1080/01621459.2013.804408OpenAlexW1984910799MaRDI QIDQ2861800

Tao Yu, Peng-Fei Li

Publication date: 11 November 2013

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2013.804408

zbMATH Keywords

diffusion tensor imagingbrain imaging\(L_1\) penaltylocally weighted least squares

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• The Adaptive Lasso and Its Oracle Properties
• One-step sparse estimates in nonconcave penalized likelihood models
• 3D space-varying coefficient models with application to diffusion tensor imaging
• Local tests for identifying anisotropic diffusion areas in human brain with DTI
• Simultaneous Confidence Bands and Hypothesis Testing in Varying-coefficient Models
• Multiscale Adaptive Regression Models for Neuroimaging Data
• Statistical Analysis of Diffusion Tensors in Diffusion-Weighted Magnetic Resonance Imaging Data
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Shrinkage Estimation of the Varying Coefficient Model
• Tuning parameter selectors for the smoothly clipped absolute deviation method
• The Estimation of Prediction Error
• Mathematical Analysis of Random Noise

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