Abstract:
Coronary Cine- Angiogram (CCA) based subjective
assessment of vascular malfunction is a preliminary diagnostic
method in Cardiac clinical procedures. Even though there are
many other medical image modalities available, improving the
CCA method to objectively detect and assess the stenosis is a
cost effective approach in Cardiac clinical procedures.
Segmentation of Coronary Arteries (CA) is a basic and
challenging area in such an endeavour. Hence, in this study we
proposed a segmentation method to extract the major areas of
CA based on Frangi's vessel enhancement filter and region
growing segmentation method called flood fill. Experimental
results of our proposed segmentation method have clearly
proven its ability to extract the main CA almost completely.
Moreover this proposed segmentation method possesses 93.73%
average segmentation accuracy. Further, it detects the vessel
path lines of the segmented frames using a thinning algorithm.
The results obtained from this proposed segmentation method
can be further enhanced to determine the functional severity of
the CA and this study lays a foundation to improve the
Coronary Angiogram image modality to do objective diagnosis
of stenosis in future.
