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Bayesian joint detection-estimation of brain activity using MCMC with a Gamma-Gaussian mixture prior model

机译：使用mCmC和伽马 - 高斯混合先验模型估计大脑活动的贝叶斯联合检测

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Salima Makni; Jérôme Idier; Jean-baptiste Poline;
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年度 2008
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1. A fully Bayesian approach to the parcel-based detection-estimation of brain activity in fMRI. [J] . Makni S, Idier J, Vincent T, NeuroImage . 2008,第3期

机译：完全贝叶斯方法用于基于功能的磁共振成像中基于包裹的脑活动检测估计。
2. Fast Joint Detection-Estimation of Evoked Brain Activity in Event-Related fMRI Using a Variational Approach [J] . Chaari L., Vincent T., Forbes F., Medical Imaging, IEEE Transactions on . 2013,第5期

机译：事件相关的功能磁共振成像中的变态方法快速联合检测-诱发脑活动的估计
3. Min-max Extrapolation Scheme for Fast Estimation of 3D Potts Field Partition Functions. Application to the Joint Detection-Estimation of Brain Activity in fMRI [J] . Laurent Risser, Thomas Vincent, Florence Forbes, Journal of VLSI signal processing systems . 2011,第3期

机译：快速估计3D Pots字段分区函数的最小-最大外推方案。在fMRI中联合检测脑活动
4. Application and validation of spatial mixture modelling for the joint detection-estimation of brain activity in fMRI [C] . Vincent, T., Ciuciu, Engineering in Medicine and Biology Society, 2007 Annual International Conference of the IEEE . 2007

机译：空间混合模型在fMRI联合检测脑活动中的应用和验证
5. Modeling joint toxicity of mixtures of organic chemicals to microorganisms in soil using quantitative structure activity relationship (QSAR) techniques. [D] . Arulgnanendran, V. Regno J. 1999

机译：使用定量结构活性关系（QSAR）技术模拟有机化学混合物对土壤中微生物的联合毒性。
6. A hybrid expectation maximisation and MCMC sampling algorithm to implement Bayesian mixture model based genomic prediction and QTL mapping [O] . Tingting Wang, Yi-Ping Phoebe Chen, Phil J. Bowman, 2016

机译：基于贝叶斯混合模型的基因组预测和QTL映射的混合期望最大化和MCMC采样算法
7. SPATIAL MIXTURE MODELLING FOR THE JOINT DETECTION-ESTIMATION OF BRAIN ACTIVITY IN fMRI [O] . Thomas Vincent, Jérôme Idier 2008

机译：用于联合检测的空间混合模型 - fmRI中脑活动的估算

Bayesian joint detection-estimation of brain activity using MCMC with a Gamma-Gaussian mixture prior model

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