In current practice, the planning volume for adjuvant brachytherapy treatment for soft-tissue sarcoma is either not determined a priori (in this case, seed locations are selected based on isodose curves conforming to a visual estimate of the planning volume), or it is derived via a tedious manual process. In either case, the process is subjective and time consuming, and is highly dependent on the human planner. The focus of the work described herein involves the development of an automated contouring algorithm to outline the planning volume. Such an automatic procedure will save time and provide a consistent and objective method for determining planning volumes. In addition, a definitive representation of the planning volume will allow for sophisticated brachytherapy treatment planning approaches to be applied when designing treatment plans, so as to maximize local tumour control and minimize normal tissue complications. An automated tumour volume contouring algorithm is developed utilizing computational geometry and numerical interpolation techniques in conjunction with an artificial intelligence method. The target volume is defined to be the slab of tissue r cm perpendicularly away from the curvilinear plane defined by the mesh of catheters. We assume that if adjacent catheters are over 2r cm apart, the tissue between the two catheters is part of the tumour bed. Input data consist of the digitized coordinates of the catheter positions in each of several cross-sectional slices of the tumour bed, and the estimated distance r from the catheters to the tumour surface. Mathematically, one can view the planning volume as the volume enclosed within a minimal smoothly-connected surface which contains a set of circles, each circle centred at a given catheter position in a given cross-sectional slice. The algorithm performs local interpolation on consecutive triplets of circles. The effectiveness of the algorithm is evaluated based on its performance on a collection of soft-tissue sarcoma tumour beds within various anatomical structures. For each of 15 patient cases considered, the algorithm takes approximately 2 min to generate the planning volume. Although the tumour shapes are rather different, the algorithm consistently generates planning volumes that visually demonstrate smooth curves compactly encapsulating the circles. This general-purpose contouring algorithm works well whether the catheters are all close together, spread far apart in the plane or arranged in a convoluted way. The automatic contouring algorithm significantly reduces labour time and provides a consistent and objective method for determining planning volumes for soft-tissue sarcoma. Further studies are needed to validate the significance of the resulting planning volumes in designing treatment plans and the role that sophisticated brachytherapy treatment planning optimization may have in producing good plans.