A Novel Implementation of Road Mapping from Digital Subtraction Angiography Images

Road Mapping (RM) is a variant of the commonly used Digital Subtraction Angiography (DSA). In this work we propose a Road Mapping algorithm in which the mask is extracted by means of vessels segmentation from DSA images. The algorithm extracts a two-dimensional map consisting of two values (black and white), to be superimposed on the live fluoroscopic image. A dedicated phantom has been created to develop the RM algorithm, simulating a circulatory system. A prototype algorithm is developed in Matlab R2018b in order to reach some preliminary results and compare different techniques. A Qt graphical interface is also developed for a fast and effective use of this new RDA approach to real veterinary fluoroscopies. Two workflows are presented, both succeeding in performing segmentation of the vessel. Their performances are compared and discussed.