Single-shell three-tissue constrained spherical deconvolution (SS3T-CSD) has been proposed to decompose the dMRI signal into three different tissue types from single-shell data. Here, we evaluate the SS3T-CSD method over a range of different situations using real data and simulations, varying parameters including SNR, partial volume effect, b-value, number of iterations, and tissue response functions. We evaluate their effect on results by comparing with the ground truth and the results estimated from MSMT-CSD. Our results indicate that while SS3T-CSD performs well, it is sensitive to some of these factors and shows some deficiencies in certain situations.
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