We combine a new user initialization process with a B-spline snake to create a model with the properties of a deformable template. This `template' snake can be constrained by its control polygon and is initially extremely close to, and similar in shape to, the target anatomical structure. The initialization process acts as almost a pre-segmentation and labelling step, making the snake's task much simpler and hence more likely to succeed in noisy images without subsequent user editing. By imposing an order on the initialization process, the user is able to transfer knowledge of global shape, symmetry, landmark position etc. to the model. We apply our snake to the segmentation of 2D medical images.