Abstract:
The coronary cine-angiogram (CCA) is an invasive
medical image modality which is used to determine the luminal
obstructions or stenosis in the Coronary Arteries (CA). CCA
based quantitative assessment of vascular morphology is a
demanding area in medical diagnosis and segmentation of blood
vessels in CCAs is one of the mandatory step in this endeavor.
The accurate segmentation of CAs in Angiogram is a challenging
task due to various reported reasons. In order to overcome this
challenge, we proposed a region growing segmentation method
which implements using morphological image processing
operations and flood fill method. It can extract the boundary of
main CA visualized in the processed CCA completely. The result
of the proposed method reveals that this proposed segmentation
method possesses 90.89% accuracy to segment the CAs related to
the selected Angiography views. This segmentation results can be
further enhanced to determine the functional severity of the CA
and this study laid the foundation to improve the Angiography
based diagnosis technique.
