We propose a new fibre tracking algorithm for cardiac DTMRI that parts with the locally "greedy" paradigm intrinsic to conventional tracking algorithms. We formulate the fibre tracking problem as the global problem of computing paths in a boolean-weighted undirected graph. Each voxel is a vertex and egdes connect every pair of neighboring voxels. We solve the underlying optimization task by Metropolis type annealing. The key features of our approach are: global optimality (unlike conventional tracking algorithms) and optimal balance between the density of fibres and the amount of available data. Besides, seed points are no longer needed; fibres are predicted in one shot for the whole DT-MRI volume without initialization artifacts.