Surface rendering and the construction of transfer functions for direct volume rendering are often based on thresholding and the resulting isosurfaces. Several approaches have been proposed to simplify the process of finding meaningful isosurface thresholds. However, optimal rendering parameters are determined in many approaches by analysis of the rendered images and not of the original volume data, thus requiring a cost-intensive thresholding/rendering optimization cycle.In this paper we present a time- and memory-efficient method for automated detection of meaningful intensity transitions between different tissue types to support visualization of CT volume data. In a single pass through the data volume a contour spectrum is determined which in particular indicates the total gradient integral of the isosurface for each possible threshold.