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Introduction. Coronary heart disease is the primary cause of sudden death in Australia, and is predicted to become the single leading health problem for the world by 2020 [1]. This disease results from an accumulation of plaque (consisting of cholesterol, calcium, and other substances) on the interior surface of arteries supplying the heart. Multi-slice spiral computed tomography angiography (MS-CTA) is emerging as a non-invasive alternative to the current "gold-standard" -- catheter-based coronary angiography (CCA) [2]. To effectively employ MS-CTA as a diagnostic tool, cardiologists use a variety of post-processing software algorithms to measure the degree of artery blockage (known as stenosis). Currently a number of algorithms exist including: oblique sectioning, curved sectioning, thin-slab maximum intensity projection (MIP), and surface rendering [3]. Methods. Unfortunately the current algorithms are inherently limited for providing insight into the complex three dimensional nature of diseased coronary arteries. These limitations stem from the two dimensional nature of these methods and/or their inability to clearly distinguish the vessel lumen from calcification artefacts. This work proposes the combined use of vessel segmentation and direct volume rendering (DVR) as a post-processing technique for more easily assessing stenosis within MS-CTA datasets. We present an initial investigation into a tracking-based vessel segmentation algorithm, coupled with direct volume rendering for visualisation. Results. A number of synthetic datasets were generated for the purpose of developing and verifying the tracking-based segmentation algorithm. Visual inspection of initial results from these synthetic datasets demonstrates the usefulness and potential of the proposed method. Further, we discuss a number of issues and present preliminary results for applying the segmentation method to real MS-CTA datasets. Conclusions. An initial investigation was undertaken into the usefulness of assessing coronary heart disease by applying vessel segmentation and direct volume rendering. Preliminary results using both synthetic and real datasets were presented and discussed. This method shows potential for allowing cardiologists to more easily visualise the complex three dimensional nature of diseased arteries, as well as providing a means to assess the true vessel lumen in the presence of calcification artefacts.