Fourier Volume Rendering (FVR) has received considerable attention in volume visualization during the last decade due its O(N2 logN) rendering time complexity, where O(N3 ) is the volume size. Nevertheless, FVR currently suffers from some quality limiting its usefulness in particular medical applications. The main reason for this is the lack of weighting sample points in dependence of the samples along the integration path. In this work we propose a solution for a special class of problems, namely the extraction and emphasis of contours in volumetric datasets. The accuracy of the illumination of the extracted contours can be derived in an exact manner. Main applications of our method include contour extraction and enhancement of features, noise removal and revealing of important spatial relationships between interior and exterior structures, making it an attractive tool for improved X-ray-like investigations of the given dataset.