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Adaptive approach to accurate analysis of small-diameter vessels in cineangiograms

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4 Author(s)
Sonka, M. ; Dept. of Electr. & Comput. Eng., Iowa Univ., Iowa City, IA, USA ; Reddy, G.K. ; Winniford, M.D. ; Collins, Steve M.

In coronary vessels smaller than 1 mm in diameter, it is difficult to accurately identify lumen borders using existing border detection techniques. Computer-detected diameters of small coronary vessels are often severely overestimated due to the influence of the imaging system point spread function and the use of an edge operator designed for a broad range of diameter vessel sizes. Computer-detected diameters may be corrected if a calibration curve for the X-ray system is available. Unfortunately, the performance of this postprocessing diameter correction approach is severely limited by the presence of image noise. The authors report here a new approach that uses a two-stage adaption of edge operator parameters to optimally match the edge operator to the local lumen diameter. In the first stage, approximate lumen diameters are detected using a single edge operator in a half-resolution image. Depending on the approximate lumen size, one of three edge operators is selected for the second full-resolution stage in which left and right coronary borders are simultaneously identified. The method was tested in a set of 72 segments of nine angiographic phantom vessels with diameters ranging from 0.46 to 4.14 mm and in 82 clinical coronary angiograms. Performance of the adaptive simultaneous border detection method was compared to that of a conventional border detection method and to that of a postprocessing diameter correction border detection method. Adaptive border detection yielded significantly improved accuracy in small phantom vessels and across all vessel sizes in comparison to the conventional and postprocessing diameter correction methods (p<0.001 in all cases). Adaptive simultaneous coronary border detection provides both accurate and robust quantitative analysis of coronary vessels of all sizes.

Published in:

Medical Imaging, IEEE Transactions on  (Volume:16 ,  Issue: 1 )