  The main contribution of this paper is to propose an iterative procedure for
tubular structure segmentation of 2D images, which combines tight frame of
Curvelet transforms with a SURE technique thresholding which is based on
principle obtained by minimizing Stein Unbiased Risk Estimate for denoising.
This proposed algorithm is mainly based on the TFA proposal presented in [1,
9], which we use eigenvectors of Hessian matrix of image for improving this
iterative part in segmenting unclear and narrow vessels and filling the gap
between separate pieces of detected vessels. The experimental results are
presented to demonstrate the effectiveness of the proposed model.
