Automatic blood vessel detection using fractional Hessian matrices

The enhancement of blood vessels is a vital stage in imaging. The goal of this project is to improve the evaluation of the performance of a method for enhancing arteries in coronary angiograms, which use fractional derivatives. In this work an algorithm for automatic enhancement of vessels in coronary angiograms is evaluated, the method uses the Hessian matrix, the eigenvalues and the Grünwald-Letnikov fractional derivative with fractional order ω the in the interval (1,3). The probes of the performance of the method were made using a set of 20 coronary angiograms with its respective ground-truth image and the area under the ROC’s curve. The fractional orders are 2<ω and the second interval 2≥ω. The results show that the maximum values of area under the ROC’s curve are obtained when the derivative order is in the interval 2<ω<2.15.