Recognition of the coronary blood vessels on angiograms using hierarchical model-based iconic search

The recognition of the coronary blood vessels on single angiograms is addressed. Recognizing blood vessels on digital subtraction angiograms is a prerequisite to automatic diagnosis and quantification of blood-vessel pathologies. It is shown how stereoscopic angiograms can improve the interpretation process. The computational strategy recommended to solve the problem has the following important characteristics. First, the model is hierarchically instantiated, starting from a partial model and working up to the final complete model. Second, the contact with the image is never broken during the interpretation process. Missing model attributes are instantiated by returning to the image. Third, delineation (segmentation and image partitioning), interpretation, and stereoscopic matching are not sequential but integrated processes. Fourth, the knowledge representation is partially iconic. The iconic memory is used to guide the search for missing or incomplete attributes in the image