Abstract:
Coronary cine-angiography is an invasive medical image modality, which is widely used in Interventional Cardiology for the detection of stenosis in Coronary arteries. Quantitative coronary analysis is one of the demanding areas in medical imaging and in this study a semi automated quantitative coronary analysis method has been proposed. Direct coronary cineangiogram frames are processed in order to obtain the features of lumen such as, vessel boundary, skeleton and luminal diameter along the vessels’ skeleton as the results. The proposed method consists of four main implementation phases namely, pre-processing, segmentation, vessel path tracking and quantitative analysis. The visual quality of the input frames is enhanced within the pre-processing phase. The proposed segmentation phase is implemented based on a spatial filtering and region growing approach. A clinically important vessel region is processed to detect the vessel boundary and skeleton, which is required as prior knowledge for quantitative analysis. Moreover, the vessel diameter is computed while tracking the vessel skeleton path starting from a given seed. The proposed segmentation method possesses 93.73% mean segmentation accuracy and 0.053 mean fallout rate. Moreover, the proposed quantitative analysis method has been validated for assessing its’ technical supportability using a clinically approved data set. As a result of that, this proposed method computes the vessel diameter along the vessel skeleton in single pixel gap and develops the ability to determine the diameter stenosis as the quantitative analysis results. Additionally, the clinical feasibility of the proposed method has been validated to emphasize the clinical usability. Moreover, this study can be further extended to make clinical decisions on stenosis through the functional significance of the vasculature by using proper medical image modality like biplane angiography.
