ï»¿Purpose: Diffusion tensor imaging enables us to visualize brain connectivity and identify white matter pathologies. Thereâs a great demand for incorporating this information into a distortion-free space by registering DTI and CT images. Here we present a multi-step method of aligning DTI datasets to CT images. Methods and Materials: To evaluate the clinical applicability of the procedure, we selected 4 patients diagnosed with brain neoplasms. Preoperatively 1,5T MR (T1W 3D: 1x1x1 mm; DTI: 1x1x3.3mm), and 16-row CT (thickness= 0.65 mm) scans were done. The initial phase consisted of registering tensors and anatomic MR images. Pre-processing steps included brain extraction from the 3D T1W volume and calculation of an isotropic image, which is a directionally averaged DWI volume. Spatial transform for the tensor registration was determined by registering the isotropic image and the masked brain. We performed the automatic 3D MR-DTI registration in 3D Slicer and used the intensity based methods of Affine Mattes MI and Deformable B-spline. Tensor alignment was achieved by running Slicerâs DTMRI module. Simultaneously, semi-automatic MRI to CT registration was executed and we applied this transformation to the MRI-aligned tensor volume. Results: We successfully performed the procedure in all subjects. The accuracy of registration was assessed by CT/T1W and T1W/parametric DTI (FA, Trace, color-by-orientation) fused images. Localization of fiber trajectories on MRI and CT volumes were inspected by experts. Conclusion: This study shows that CT-registered DTI may play an important role in applications that require precise spatial orientation, like during radiosurgery or stereotactic interventions.