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<p>The coronary tree expert (CORTEX) analyzer, which is a vision system for the description of the bidimensional shape and position of coronary vessels using standard nonsubtracted radiographic images, is described. A bottom-up approach was used to deal with the typical characteristics of medical images, such as structural and nonstructural noise and complexity and variability of biological shapes. On these grounds, grouping criteria were utilized to produce intermediate image representations with an increasing complexity in a hierarchical manner (from edge points to curves, segments, bars, and finally to vessels and their mutual relations). In this way, uncertain, inconsistent, and deficient information was efficiently processed. The evaluation of CORTEX segmentation is also performed according to a signal-detection-theory-like approach.</p>
coronary tree expert analyzer; CORTEX structural noise; artificial vision system; X-ray images; human coronary trees; bidimensional shape; nonsubtracted radiographic images; bottom-up approach; medical images; nonstructural noise; biological shapes; grouping criteria; intermediate image representations; edge points; curves; segmentation; signal-detection-theory-like approach; cardiology; computer vision; diagnostic radiography; expert systems; image segmentation; medical image processing
R. Poli, M. Demi, G. Coppini, G. Valli, "An Artificial Vision System for X-ray Images of Human Coronary Trees", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 15, no. , pp. 156-162, February 1993, doi:10.1109/34.192487
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