A method for planning treatment for arterial stenotic lesions for generating quantitative information that automatically suggests an optimal stent configuration for treating a patient's stenotic lesions, comprising: 1.1 identifying a set of stenotic lesions in a patient's coronary arteries from medical image data of the patient; 1.2 generating a plurality of treatment options for the set of stenotic lesions, wherein each of the plurality of treatment options corresponds to a stenting configuration in which one or more of the stenotic lesions are stented; and 1.3 calculating, for each of the plurality of treatment options, predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option; and 1.4 displaying a model of the patient's coronary arteries; and 1.5 in response to a user selecting an entry corresponding to a treatment option in a table of treatment options, displaying the stenting configuration corresponding to the selected treatment option and the hemodynamic metrics calculated for the set of stenotic lesions resulting from the stenting configuration corresponding to the selected treatment option using machine learning or computer based simulation of blood flow and pressure, 1.6 in response to a user selection of one or more stent locations on the model of the patient's coronary arteries, displaying the hemodynamic metrics calculated for the set of stenotic lesions for a treatment option corresponding to the stenting configuration indicated by the user selection of the one or more stent locations; and 1.7 ranking the plurality of treatment options based on the predicted hemodynamic metrics for the set of stenotic lesions calculated for each of the plurality of treatment options and a number of stents in the stenting configuration corresponding to each of the plurality of treatment options, wherein the ranking is further specified in that the plurality of treatment options is ranked in order of maximal blood flow restoration based on the predicted hemodynamic metrics calculated for the set of stenotic lesions, with treatment options having stenting configurations with a smaller number of stents ranked ahead of treatment options having stenting configurations with a larger number of stents if the predicted hemodynamic metrics calculated for the treatment options having the stenting configurations with the smaller number of stents indicate that a blood flow is sufficiently restored. 1.1 identifying a set of stenotic lesions in a patient's coronary arteries from medical image data of the patient; 1.2 generating a plurality of treatment options for the set of stenotic lesions, wherein each of the plurality of treatment options corresponds to a stenting configuration in which one or more of the stenotic lesions are stented; and 1.3 calculating, for each of the plurality of treatment options, predicted hemodynamic metrics for the set of stenotic lesions resulting from the stenting configuration corresponding to that treatment option; and 1.4 displaying a model of the patient's coronary arteries; and 1.5 in response to a user selecting an entry corresponding to a treatment option in a table of treatment options, displaying the stenting configuration corresponding to the selected treatment option and the hemodynamic metrics calculated for the set of stenotic lesions resulting from the stenting configuration corresponding to the selected treatment option using machine learning or computer based simulation of blood flow and pressure, 1.6 in response to a user selection of one or more stent locations on the model of the patient's coronary arteries, displaying the hemodynamic metrics calculated for the set of stenotic lesions for a treatment option corresponding to the stenting configuration indicated by the user selection of the one or more stent locations; and 1.7 ranking the plurality of treatment options based on the predicted hemodynamic metrics for the set of stenotic lesions calculated for each of the plurality of treatment options and a number of stents in the stenting configuration corresponding to each of the plurality of treatment options, wherein the ranking is further specified in that the plurality of treatment options is ranked in order of maximal blood flow restoration based on the predicted hemodynamic metrics calculated for the set of stenotic lesions, with treatment options having stenting configurations with a smaller number of stents ranked ahead of treatment options having stenting configurations with a larger number of stents if the predicted hemodynamic metrics calculated for the treatment options having the stenting configurations with the smaller number of stents indicate that a blood flow is sufficiently restored.