FMRI ANALYSIS THROUGH BAYESIAN VARIABLE SELECTION WITH A SPATIAL PRIOR

机译：通过使用空间的贝叶斯变量选择FMRI分析

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This paper presents a novel spatial Bayesian method for simultaneous activation detection and hemodynamic response function (HRF) estimation of functional magnetic resonance imaging (fMRI) data. A Bayesian variable selection approach is used to induce shrinkage and sparsity, with a spatial prior on latent variables representing activated hemodynamic response components. Then, the activation map is generated from the full spectrum of posterior inference constructed through a Markov chain Monte Carlo scheme, and HRFs at different voxels are estimated non-parametrically with information pooling from neighboring voxels. By integrating functional activation detection and HRFs estimation in a unified framework, our method is more robust to noise and less sensitive to model mis-specification.

机译：本文介绍了一种新型空间贝叶斯方法，用于同时激活检测和血液动力响应函数（HRF）估计功能磁共振成像（FMRI）数据的估计。贝叶斯变量选择方法用于诱导收缩和稀疏性，在潜在变量上具有表示激活的血液动力学响应组件的空间。然后，从通过Markov链蒙特卡罗方案构成的全谱产生激活图，并且在不同体素处的HRF与来自相邻体素的信息汇率估计。通过在统一的框架中积分功能激活检测和HRFS估计，我们的方法对噪声更加坚固，对模型错误规范不太敏感。

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《IEEE International Symposium on Biomedical Imaging》|2009年||共4页
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作者
Jing Xia; Feng Liang; Yongmei Michelle Wang;
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中图分类 TP391.41-53;
关键词
Bayesian variable selection; Hemodynamic response function; Activation detection; Spatial prior; Markov chain Monte Carlo (MCMC);

机译：贝叶斯变量选择;血液动力学响应功能;激活检测;空间先前;马尔可夫链蒙特卡罗（MCMC）;

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专利

1. Classification of brain activation via spatial Bayesian variable selection in fMRI regression [J] . Stefanie Kalus, Philipp G. S?mann, Ludwig Fahrmeir Advances in data analysis and classification . 2014,第1期

机译：在功能磁共振成像中通过空间贝叶斯变量选择对大脑激活进行分类
2. Fast Bayesian whole-brain fMRI analysis with spatial 3D priors [J] . Siden Per, Eklund Anders, Bolin David, NeuroImage . 2017,第期

机译：快速贝叶斯全脑FMRI分析与空间3D前衣
3. Bayesian fMRI data analysis with sparse spatial basis function priors. [J] . Flandin G, Penny WD NeuroImage . 2007,第3期

机译：具有稀疏空间基函数先验的贝叶斯fMRI数据分析。
4. FMRI ANALYSIS THROUGH BAYESIAN VARIABLE SELECTION WITH A SPATIAL PRIOR [C] . Jing Xia, Feng Liang, Yongmei Michelle Wang IEEE International Symposium on Biomedical Imaging . 2009

机译：通过使用空间的贝叶斯变量选择FMRI分析
5. Spatial Bayesian variable selection and fMRI. [D] . McEvoy, Bradley Wright. 2009

机译：空间贝叶斯变量选择和功能磁共振成像。
6. Bayesian Analysis of fMRI Data with ICA Based Spatial Prior [O] . Deepti R. Bathula, Hemant D. Tagare, Lawrence H. Staib, -1

机译：基于ICA的空间先验的fMRI数据的贝叶斯分析。
7. Anatomically Informed Bayesian Spatial Priors for FMRI Analysis [O] . David Abramian, Per Siden, Hans Knutsson, 2020

机译：解剖学上通知的贝叶斯空间前沿进行FMRI分析

FMRI ANALYSIS THROUGH BAYESIAN VARIABLE SELECTION WITH A SPATIAL PRIOR

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