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In this paper, a cluster-based framework is introduced for comparing analysis methods of functional magnetic resonance images (fMRI). In the proposed framework, fMRI data is repla...
Abstract—Functional magnetic resonance images (fMRI’s) provide high-resolution datasets which allow researchers to obtain accurate delineation and sensitive detection of activa...
Xavier Descombes, Frithjof Kruggel, D. Yves von Cr...
In functional Magnetic Resonance Imaging (fMRI) data analysis, normalization of time series is an important and sometimes necessary preprocessing step in many widely used methods. ...
Jian Cheng, Feng Shi, Kun Wang, Ming Song, Jiefeng...
Independent Component Analysis is becoming a popular exploratory method for analysing complex data such as that from FMRI experiments. The application of such `model-free' me...
In this paper, we study Markov Random Fields as spatial smoothing priors in fMRI detection. Relatively high noise in fMRI images presents a serious challenge for the detection algo...