Non-Gaussian Anisotropic Diffusion Processing for Medical Imagining Using the OsiriX DICOM Viewer

Medical imaging is a fertile area for computer graphics, image processing and real time visualization. In this paper we present a method for reducing noise in CT (Computed Tomography) and MR (Magnetic Resonance) images that (in addition to other noise sources) is characteristic of the numerical procedures required to construct the images, namely, the (inverse) Radon Transform. In both cases, MR imaging in particular, an additional noise source is due to the process of diffusion thereby predicating use of the Anisotropic Diffusion method for noise suppression. This method is based on a diffusion model for noise generation where the Diffusivity is taken to be non-isotropic (inhomogeneous) or anisotropic and is, in the absence of a priori information, computed through application of an edge detection algorithm. In this paper we extend the approach to include theeffect of fractional diffusion (when the underlying statistical model associated with the diffusion process is non-Gaussian) and derive a corresponding Finite Impulse Response Filter. The algorithms developed are implemented using the OsiriX DICOM (Digital Imaging and Communications in Medicine), a high performance open source image data visualization system for the development of processing and visualization tools