Adaptive segmentation of 3D volumes

Boštjan Čotar (2014) Adaptive segmentation of 3D volumes. EngD thesis.

Preview

PDF Download (3007Kb)

Abstract

The main objective of the thesis was to develop a method for segmentation of a 3D vascular tree model for the program NeckVeins. By comparing the threshold value with the value of each vertex of the segment, which is a voxel, the method determines which voxels represent the main body of the vein tree, which represent the background and which represent the so-called »neighbours«. Depending on how detailed we want to plot the 3D model, the method recursively divides the adjacent voxels to eight smaller voxels. For each of the smaller segment we re-determine to which category it belongs, so that in the end the vein tree model is built from voxels of different sizes. The newly developed algorithm is implemented in the program NeckVeins, which itself already contains its own segmentation method. We compare the differences between the algorithms using screenshots of the 3D vascular model, paying attention to the structure of the blood vessel, staircasing and the accuracy of the plot.

Actions (login required)