SEGMENTATION

Segmentation can be performed manually or
(semi)automatically. Segmentation algorithms are
often based on the principle of region growing
. Placing one or more seed points initiates the
segmentation of the target structure. From these
seed points, more and more neighboring voxels
that fulfill predefined criteria are included in the
segmentation . The technique can be applied
in two ways: segmentation of the desired tissue or
segmentation of the undesired tissue with subsequent
removal from the data. The latter method
removes only interfering tissue (bone or densely
enhanced veins) from the CT angiography data
and retains soft tissue as well as contrast-enhanced
vessels for further evaluation. To refine
the boundary of the segmented structures, morphologic
dilation operations may be applied.
A particular problem in threshold-based segmentation
algorithms are areas with close contact
of two tissue types with comparable attenuation,
such as bone and contrast-enhanced vessels
(course of the ICA through the skull base; intraforaminal
sections of the vertebral artery)
. Although the process of segmentation is
semiautomatic, user interaction is necessary to set
additional seeding points or to intervene in cases
of inclusion of neighboring structures due to leakage
of the region-growing algorithm. These procedures
can be time-consuming and may exceed
practical limits in routine clinical work flow.