Accurate analysis of angiograms based on 3D vector field topology

Cardiovascular diseases are still the number one killer in the United States. The typical diagnostic method is using angiograms for detecting these types of diseases. As is the case with many diseases, early detection can help reduce further progression or enable physicians to take counter measures early on. Hence, accurate analysis techniques are needed for processing these angiogram data sets. In order to perform such analysis of CTA (Computed Tomography Angiograms) data sets, accurate measurements of the coronary vasculature have to be extracted from the volumetric data, such as vessel length, vessel bifurcation angles, cross-sectional area, and vessel volume. These measurements can then be used to discriminate healthy cases from diseased cases. Therefore, this article describes an improved segmentation algorithm based on a hybrid approach between iso-value and image-gradient segmentation and a center line extraction method utilizing 3D vector field topology analysis. Based on the center lines of the coronary vessels found in the angiogram, the quantitative measurements are then computed that can help in the diagnostic process.

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► We analyze CT angiograms to detect cardiovascular disease.
► Arterial vessels are segmented by combining iso-value and image-gradient segmentation.
► Based on a 3D topological analysis, center lines of the arteries are identified.
► Quantitative measurements can be accurately extracted.
► A comparison of healthy and diseased patients shows the strengths of the approach.