ABSTRACT
A method is proposed that performs a temporal tracking of the coronaries in multi-slice computed tomography (MSCT) dynamic sequences. The process exploits geometric moments and a local cylindrical approximation of the vessel to estimate the local characteristics of the structure in each volume and estimate its displacement along the sequence. The research strategy is based on a region matching process to find the location of the point in the successive volumes. A spatial tracking is then applied to refine its location inside the vessel. Tests have been achieved on simulated and real displacements of coronary segments.
Subject(s)
Coronary Angiography/methods , Coronary Vessels , Heart/diagnostic imaging , Image Processing, Computer-Assisted , Myocardial Contraction , Tomography, X-Ray Computed/methods , HumansABSTRACT
An algorithm is proposed that perform a temporal tracking of the vessel central axis in a 3-D dynamic sequence in multi-slice computed tomography (MSCT). The approach is based on geometric moments and a local cylindrical approximation. The local characteristics of the vessel are estimated on the first volume of the sequence (position on the vessel central axis, local diameter, intravascular and background intensities), then used to track the vessel along the sequence. The correspondence between two volumes is solved through a region matching based on a criterion of minimal distance combining moment-based descriptors with intensity information. Preliminary results are presented on two sequences.
Subject(s)
Algorithms , Coronary Angiography/methods , Imaging, Three-Dimensional/methods , Pattern Recognition, Automated/methods , Radiographic Image Enhancement/methods , Radiographic Image Interpretation, Computer-Assisted/methods , Tomography, X-Ray Computed/methods , Artificial Intelligence , Coronary Angiography/instrumentation , Humans , Reproducibility of Results , Sensitivity and Specificity , Time Factors , Tomography, X-Ray Computed/instrumentationABSTRACT
An improved and very fast algorithm dealing with the extraction of vessels in three-dimensional imaging is described. The approach is based on geometrical moments and a local cylindrical approximation. A robust estimation of vessel and background intensity levels, position, orientation, and diameter of the vessels with adaptive control of key parameters, is provided during vessel tracking. Experimental results are presented for lower limb arteries in multidetector computed tomography scanner.
