A computer-implemented method for providing quantitative airway information (INFO1), comprising: - determining (DET-1) first medical image data of an airway segment (AS1, AS2), - applying (APP-1) a first trained function to the first medical image data, wherein output data is generated, - determining (DET-2) the one quantitative airway information (INFO1) of the airway segment (AS1, AS2) based on the output data, - providing (PROV-1) the at least one quantitative airway information (INFO1), wherein the first medical image data is extracted from the second medical image data, wherein the first medical image data is two-dimensional and the second medical image data is three-dimensional, wherein the step of determining (DET-1) the first medical image data comprises: - receiving (REC-2) a second medical image data, - applying (APP-2) a second trained function to the second medical image data, wherein an airway probability map (PROB1) is generated, - applying (APP-3) a skeletonization algorithm on the airway probability map (PROB1) determining an airway centerline tree (CTREE1), wherein the first medical image data is determined based on the airway centerline tree (CTREE1) and the second medical image data, wherein the airway segment is a subsection of the airway depicted in the second medical image data, extended along a centerline segment, wherein the centerline segment is a part of the airway centerline tree, wherein the first medical image data is a slice of the second medical image data, wherein the slice is orthogonal with respect to the part of the airway centerline tree corresponding to the airway segment, wherein the airway segment is projected onto the slice along the centerline segment. - determining (DET-1) first medical image data of an airway segment (AS1, AS2), - applying (APP-1) a first trained function to the first medical image data, wherein output data is generated, - determining (DET-2) the one quantitative airway information (INFO1) of the airway segment (AS1, AS2) based on the output data, - providing (PROV-1) the at least one quantitative airway information (INFO1), wherein the first medical image data is extracted from the second medical image data, wherein the first medical image data is two-dimensional and the second medical image data is three-dimensional, wherein the step of determining (DET-1) the first medical image data comprises: - receiving (REC-2) a second medical image data, - applying (APP-2) a second trained function to the second medical image data, wherein an airway probability map (PROB1) is generated, - applying (APP-3) a skeletonization algorithm on the airway probability map (PROB1) determining an airway centerline tree (CTREE1), - receiving (REC-2) a second medical image data, - applying (APP-2) a second trained function to the second medical image data, wherein an airway probability map (PROB1) is generated, - applying (APP-3) a skeletonization algorithm on the airway probability map (PROB1) determining an airway centerline tree (CTREE1), wherein the first medical image data is determined based on the airway centerline tree (CTREE1) and the second medical image data, wherein the airway segment is a subsection of the airway depicted in the second medical image data, extended along a centerline segment, wherein the centerline segment is a part of the airway centerline tree, wherein the first medical image data is a slice of the second medical image data, wherein the slice is orthogonal with respect to the part of the airway centerline tree corresponding to the airway segment, wherein the airway segment is projected onto the slice along the centerline segment.