Methods and apparatus for biomedical data analysis to produce enhanced images of tubular structures are disclosed. A Gaussian convolution of an input image is used to calculate a Hessian matrix. An Eigen decomposition of the Hessian matrix produces eigenvectors and eigenvalues, which are sorted to determine bright tubular structure detection according to high and low values that represent brightness, and structure shape. A tubularity computation calculates the probability of a voxel of interest being part of a tubular network. Embodiments may be implemented to share computer resources such as between a computer processing unit (CPU) and a graphic processing unit (GPU).