A new filtering algorithm for medical magnetic resonance and computer tomography images

Abstract

Inner views of tubular structures based on computer tomography (CT) and magnetic resonance (MR) data sets may be created by virtual endoscopy. After a preliminary segmentation procedure for selecting the organ to be represented, the virtual endoscopy is a new postprocessing technique using surface or volume rendering of the data sets. In the case of surface rendering, the segmentation is based on a grey level thresholding technique. To avoid artifacts owing to the noise created in the imaging process, and to restore spurious resolution degradations, a robust Wiener filter was applied. This filter working in Fourier space approximates the noise spectrum by a simple function that is proportional to the square root of the signal amplitude. Thus, only points with tiny amplitudes consisting mostly of noise are suppressed. Further artifacts are avoided by the correct selection of the threshold range. Afterwards, the lumen and the inner walls of the tubular structures are well represented and allow one to distinguish between harmless fluctuations and medically significant structures.