Fractional flow reserve score estimation method and device based on graph neural network

The invention provides a fractional flow reserve estimation method and device based on a graph neural network, and the method comprises the steps: obtaining a contrastographic image of a target coronary artery, and determining the prior information of the target coronary artery according to the contrastographic image; condition features constrained by the target coronary artery topology are determined according to the prior information; generating a blood pressure prediction value and a blood flow prediction value of the target coronary artery according to the prior information and the condition characteristics; and generating the fractional flow reserve of the target coronary artery according to the blood pressure predicted value and the blood flow predicted value. When the FFR is calculated, only non-invasive imaging data is needed, and invasive examination is avoided; compared with an existing CFD model, the method has the advantages that the deep learning method is combined, the fractional flow reserve ca