Abstract: Method for quantitative analysis of a tree or part of a tree of recursively splitting tubular organs, the method comprising the following steps: —providing a 3D model of said tree or part of said tree, such 3D model giving a representation of the surface of the lumen wall of the tubular organs forming the tree or part of the tree; —defining the 3D centerlines of said tree or part of the tree; —identifying the branches of the tree; —identifying N-furcations of the tree or part of the tree, an N-furcation being a part of the tree where a proximal tubular organ branches into two or more distal tubular organs, further comprising the step of: —dividing, independently from the modality used for obtaining the 3D model, each branch in one or more regions, such regions being of two different types, named single vessel region and splitting region, different cross-section surfaces being defined in such regions, wherein the splitting regions can exist at the proximal side of a branch as well as at the distal side of said

Abstract: Method for quantitative analysis of a tree or part of a tree of recursively splitting tubular organs, the method comprising the following steps:—providing a 3D model of said tree or part of said tree, such 3D model giving a representation of the surface of the lumen wall of the tubular organs forming the tree or part of the tree;—defining the 3D centrelines of said tree or part of the tree;—identifying the branches of the tree;—identifying N-furcations of the tree or part of the tree, an N-furcation being a part of the tree where a proximal tubular organ branches into two or more distal tubular organs, further comprising the step of:—dividing, independently from the modality used for obtaining the 3D model, each branch in one or more regions, such regions being of two different types, named single vessel region and splitting region, different cross-section surfaces being defined in such regions, wherein the splitting regions can exist at the proximal side of a branch as well as at the distal side of said bran

Abstract: A computer-implemented method (and corresponding data processing facility and computer program) for creating a 3D bifurcation healthy model from multiple 2D angiographic images comprises the following: a. Creating a 3-D model based on said images; b. Defining a bifurcation region regarding said 3D model; c. Creating an area curve regarding said region; d. Creating a reference area curve regarding said region whilst reconstructing in 2D; e. Creating a healthy model regarding said area curves; and f. Computing quantitative analysis results regarding said healthy model based on the healthy cross-sectional areas of the bifurcation, obstruction boundaries and the diseased 3D model consisting of the bifurcation centerlines and cross-sections of the lumen on the centerline, the healthy centerline and cross-sections.

Abstract: A method, data processing facility and program storage device for quantitative analysis on medical image data of a bifurcated tubular organ which involves processing the medical image data to identify contours of the bifurcated tubular organ. The contours are used to determine a Polygon of Confluence amongst the bifurcated tubular organ. The Polygon of Confluence is used to determine at least one parameter value characterizing geometry of the bifurcated tubular organ. The at least one parameter value is outputted to a user for angiography purposes. The at least one parameter value can include at least one diameter value of the bifurcated tubular organ, at least one angle value between parts of the bifurcated tubular organ, and at least one reference diameter value for the bifurcated tubular organ, the at least one reference diameter value compensating for damage to the bifurcated tubular organ.

Abstract: A computer-implemented method (and corresponding data processing facility and computer program) for creating a 3D bifurcation healthy model from multiple 2D angiographic images comprises the following: a. Creating a 3-D model based on said images; b. Defining a bifurcation region regarding said 3D model; c. Creating an area curve regarding said region; d. Creating a reference area curve regarding said region whilst reconstructing in 2D; e. Creating a healthy model regarding said area curves; and f. Computing quantitative analysis results regarding said healthy model based on the healthy cross-sectional areas of the bifurcation, obstruction boundaries and the diseased 3D model consisting of the bifurcation centerlines and cross-sections of the lumen on the centerline, the healthy centerline and cross-sections.