Contour and Centreline Tracking of Vessels from Angiograms using the Classical Image Processing Techniques
This is an incremental approach for medical imaging analysis in cardiac catheterism, with potential use in measuring vessel length or radius.
The paper tackled vessel edge and centerline detection in angiograms using classical image processing techniques, achieving accuracy for images with good spatial resolution (512*512).
This article deals with the problem of vessel edge and centerline detection using classical image processing techniques due to their simpleness and easiness to be implemented. The method is divided into four steps: the vessel enhancement which implies a non-linear filtering proposed by Frangi, the thresholding using Otsu method and the contour detection using the Canny edge detector due to its good performances for the small vessels and the morphological skeletonisation. The algorithms are tested on real data collected from a cardiac catheterism laboratory and it is accurate for images with good spatial resolution (512*512). The output image can be used for further processing in order to find the vessel length or its radius.