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Accurate tracking of blood vessels and EEG electrodes by consecutive cross-section matching

We discuss the quality by which image algorithms are able to characterize 3D line structure, like blood vessels, nerves, chromosomes, electrodes, etc. In the study, the methods are examined how well they can determine the axial position, local intensity, local diameter, or local orientation under conditions of noise, bifurcations and neighbor structures. We present the Consecutive Cross-Section Matching (CCSM) method, and compare it with the global method of Lorentz and the local slice method of Zhou. When applying the methods on a circular test image and 3D phase-contrast MR angiography image, we find that the Lorentz method gives reasonable estimates for the width of the line-structures, but has large difficulties to pass bifurcations. The local slice method is more accurate but is sensitive to noise. As the CCSM method takes more samples along the axis, the CCSM method appears to be much more accurate and robust in characterizing line-structures.