Abstract: An accurate analysis of the spatial distribution and intravascular pattern of blood flow in any organ must be based on detailed morphometry (diameters, lengths, vessel numbers, branching pattern, branching angles, etc.) of the organ vasculature. Despite the significance of detailed morphometric data, there is relative scarcity of database on vascular anatomy, mainly because the process is extremely labor intensive. Novel methods in the form of a segmentation algorithm for semi-automation of morphometric data extraction are provided. The extraction algorithm is based on a topological analysis of a vector field generated by the normal vectors of the extracted vessel wall. With this approach, special focus is made on achieving the highest accuracy of the measured values, with excellent results when compared to manual measurements of the main trunk of the coronary arteries with microscopy.

Abstract: An accurate analysis of the spatial distribution and intravascular pattern of blood flow in any organ must be based on interpolated gradient located within back plane detailed morphometry (diameters, lengths, of cube defined by neighboring voxels vessel numbers, branching pattern, branching angles, etc.) of the organ vasculature. Despite the significance of detailed morphometric data, there is relative scarcity of database on vascular anatomy, mainly because the process is extremely labor intensive. Novel methods in the form of a segmentation algorithm for semi-automation of morphometric data extraction are provided. The extraction algorithm is based on a topological analysis of a vector field generated by the normal vectors of the extracted vessel wall. With this approach, special focus is made on achieving the highest accuracy of the measured values, with excellent results when compared to manual measurements of the main trunk of the coronary arteries with microscopy.

Abstract: An accurate analysis of the spatial distribution and intravascular pattern of blood flow in any organ must be based on detailed morphometry (diameters, lengths, vessel numbers, branching pattern, branching angles, etc.) of the organ vasculature. Despite the significance of detailed morphometric data, there is relative scarcity of database on vascular anatomy, mainly because the process is extremely labor intensive. Novel methods in the form of a segmentation algorithm for semi-automation of morphometric data extraction are provided. The extraction algorithm is based on a topological analysis of a vector field generated by the normal vectors of the extracted vessel wall. With this approach, special focus is made on achieving the highest accuracy of the measured values, with excellent results when compared to manual measurements of the main trunk of the coronary arteries with microscopy.