Diffusion tensor imaging (DTI) data has traditionally been displayed as a grayscale functional anisotropy map (GSFM) or color coded orientation map (CCOM). These methods use black and white or color with intensity values to map the complex multidimensional DTI data to a two-dimensional image. Alternative visualization techniques, such as maps utilize enhanced graphical representation of the principal eigenvector by means of a headless arrow on regular nonstereoscopic (VM) or stereoscopic display (VMS). A survey of clinical utility of patients with intracranial neoplasms was carried out by 8 neuroradiologists using traditional and nontraditional methods of DTI display. Pairwise comparison studies of 5 intracranial neoplasms were performed with a structured questionnaire comparing GSFM, CCOM, VM, and VMS. Six of 8 neuroradiologists favored maps over traditional methods of display (GSFM and CCOM). When comparing the stereoscopic (VMS) and the non-stereoscopic (VM) modes, 4 favored VMS, 2 favored VM, and 2 had no preference. In conclusion, processing and visualizing DTI data stereoscopically is technically feasible. An initial survey of users indicated that based display methodology with or without stereoscopic visualization seems to be preferred over traditional methods to display DTI data. 1. Introduction Diffusion tensor imaging (DTI) is a magnetic resonance (MR) imaging technique that enables the quantitative measurement of molecular diffusion in biologic tissues in vivo [1–7]. Diffusion signal changes are caused by the anisotropy (or directionality) of WM fibers; the fibers restrict water molecule movement across the axons while leaving movement along the axons relatively unrestricted. This results in unequal (or anisotropic) diffusivities along the axons. The ability to measure these very specific tissue characteristics in vivo is unique to DTI and has many applications in clinical neuroimaging including the delineation of tumor infiltration, assessing the integrity of neuronal fibers and neurosurgical planning [8–19]. Many techniques and schemes have been proposed for visualizing DTI data [20–28] such as using ellipsoids with their principal axes corresponding to the eigenvectors and using volumetric rendering or shading to present these ellipsoids’ directional information [23]. These are rigorous approaches but are still subject to the limiting problems of any technique that visualizes 3D information in two dimensions (2D). Often the 3D shading of diffusion tensor ellipsoids [23] or superquadric glyphs [24] at all voxels does not give a global view
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