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» Modeling Adaptation Effects in fMRI Analysis
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IPMI
2011
Springer
12 years 10 months ago
Generalized Sparse Regularization with Application to fMRI Brain Decoding
Many current medical image analysis problems involve learning thousands or even millions of model parameters from extremely few samples. Employing sparse models provides an effecti...
Bernard Ng, Rafeef Abugharbieh
TMI
2010
182views more  TMI 2010»
13 years 5 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern
MICCAI
2005
Springer
14 years 8 months ago
Physiological System Identification with the Kalman Filter in Diffuse Optical Tomography
Abstract. Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxyand deoxyhemoglobin. When applied to functiona...
Solomon Gilbert Diamond, Theodore J. Huppert, Vill...
ISBI
2007
IEEE
14 years 1 months ago
An Effective and Efficient Technique for Searching for Similar Brain Activation Patterns
In this paper, we introduce a new approach for content-based similarity search for brain images. Based on the keyblock representation, our framework employs the Principal Componen...
Jingjing Zhang, Vasileios Megalooikonomou
ICASSP
2007
IEEE
14 years 1 months ago
A Multi-Subject, Dynamic Bayesian Networks (DBNS) Framework for Brain Effective Connectivity
As dynamic connectivity is shown essential for normal brain function and is disrupted in disease, it is critical to develop models for inferring brain effective connectivity from ...
Junning Li, Z. Jane Wang, Martin J. McKeown