Abstract

In this paper, we investigate the incorporation of in-dependent component analysis (ICA) with Q-ball imaging (QBI)to extract information on the diffusion orientation distributionfunction (ODF) from an inner voxel. In our approach, the ICAalgorithm is applied to a mixture of ODFs which are constructedbased on the analytical QBI solution. The numerical simulationresults demonstrate that the proposed ICA framework can notonly successfully separate the diffusion ODF from the noisydiffusion data, but also achieves better performance comparedwith a QBI solution when the data has a low signal to noise ratio (SNR).