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Fibre tractography using diffusion tensor imaging allows the study of anatomical connectivity of the brain, and is an important diagnostic tool for a range of neurological diseases. Deterministic tractography algorithms assume that the fibre direction coincides with the principal eigenvector of a diffusion tensor. This is, however, not the case for regions with crossing fibres. In addition noise introduces uncertainty and makes the computation of fibre directions difficult. Stochastic tractography algorithms have been developed to overcome the uncertainties of deterministic algorithms. However, generally, both parametric and non-parametric stochastic algorithms require longer computational time and large amounts of memory. Multi-tensor fibre tracking methods can alleviate the problems when crossing fibres are encountered. In this study simple and computationally efficient random-walk algorithms are described for estimating anatomical connectivity in white matter. These algorithms are then applied to a two-tensor model to compute the probabilities of connections between regions with complex fibre configurations. We analyze the random-walk models quantitatively using simulated data and estimate the optimal parameter values of the models. The performance of the tracking algorithms is verified using a physical phantom and an in vivo dataset with a wide variety of seed points. The results confirm the effectiveness of the proposed approach, which gives comparable results to other stochastic methods. Our approach is however significantly faster and requires less memory. The results of two-tensor random-walk algorithms demonstrate that our algorithms can accurately identify fibre bundles in complex fibre regions.

Image guided neurosurgery is becoming more widely used as conventional stereotactic techniques are replaced by frameless systems which allow flexible but accurate positioning of surgical approach routes with reduced invasiveness. We have developed a surgical planning and guidance system (VISLAN) which uses stereo video to construct an Intra-Operative Patient Representation (IOPR) and to track a hand-help locator in real time. The IOPR is automatically registered with the Pre-Operative Patient Representation (POPR), which is constructed from MR and other modalities and also includes the surgical plan. Images combining POPR and IOPR objects guide the surgeon on his pre-planned path towards the target.© (1994) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

We present a graph-based approach to the production of hierarchical segmentations of grey- level images. The technique is designed to be as responsive as possible to the structure of the image but general in the sense that it is independent of the exact edge measure used. We present results using a novel edge measure which combines the first and second derivatives of the image to calculate the phase of the image with respect to scale. We combine this with the gradient to produce a value which reflects both the strength and the stability of candidate edges.

An efficient scheme for representation of the shape of anatomical and pathological structures is required for intelligent computer interpretation of medical images. We present an approach to the extraction and representation of shape which, unlike previous shape representations, does not require complete boundary descriptions. It is based on the `Delaunay triangulation' and its dual the `Voronoi diagram.' Our method of using this dual leads to both a skeleton description and a boundary description. The basic step in the algorithm is that of deciding whether to treat any pair of neighboring points as adjacent (lying next to each other on the same boundary) or opposite (lying on opposing sides of a skeleton separating two boundaries). The duality of the skeleton and boundary descriptions produced means that the splitting of one object into two separate objects, or the merging of two objects into one, can be easily accomplished.© (1992) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.