To address the potential of the iterative technique to improve the SM of general structures such as the basal ganglia, a 3D model of the brain was created including the: red nucleus (RN), substantia nigra (SN), crus cerebri (CC), thalamus (TH), caudate nucleus (CN), putamen (PUT), globus pallidus (GP), grey matter (GM), white matter (WM), cerebrospinal fluid (CSF) and the major vessels [34 ]. The structures in the 3D brain model were extracted from two human 3D T1 weighted and T2 weighted data sets. Basal ganglia and vessels are from one person; grey matter and white matter are from the other person’s data set. Since all structures are from in vivo human data sets, this brain model represents realistic shapes and positions of the structures in the brain. Susceptibility values in parts per million (ppm) for the structures SN, RN, PUT and GP, were taken from ref. [12 (link)] and others were from measuring the mean susceptibility value in a particular region from SMs using ref. [18 (link)] from in vivo human data: RN = 0.13, SN = 0.16, CC = −0.03, TH = 0.01, CN = 0.06, PUT = 0.09, GP = 0.18, vessels = 0.45, GM = 0.02, CSF = −0.014 and WM=0. All structures were set inside a 512×512×256 matrix of zeros. The phase of the 3D brain model was created by applying the forward method [8 (link),26 ,27 ,32 (link)] to the 3D brain model with different susceptibility distributions using the imaging parameters: TE = 5ms and B0 = 3T. A comparison between the phase maps from this brain model and a real data set is shown in Fig.3. To match the imaging parameters of the real data set, B0=3T and TE=18ms were applied for the results presented in Fig.3. Except for Fig.3, all other figures in the paper associated with the 3D brain were simulated by using TE=5ms.