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Three dimensional structure recognition in digital angiograms using Gauss-Markov methods

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3 Author(s)
Petrocelli, R.R. ; Miriam Hospital Div. of Cardiology, Brown Univ., Providence, RI, USA ; Manbeck, K.M. ; Elion, J.L.

Existing methods for automatically finding arteries in coronary angiograms rely on preprocessing (digital subtraction or edge enhancement). Structure recognition in unprocessed images will enable the analysis of a wider range clinical images (of varying quality). The authors have previously reported on a prototype which works on such unsubtracted and unprocessed digital angiograms. They now present a system designed to process image pairs and thereby perform recognition in three dimensions. This approach, the “Deformable Template Matcher” (DTM), combines a-priori knowledge of the arterial tree (encoded as mathematical “templates”) with a stochastic deformation process described by a hidden Markov model. An introduction so the technique is presented along with examples of its application to bi-plane images and a discussion of the computational implications

Published in:

Computers in Cardiology 1993, Proceedings.

Date of Conference:

5-8 Sep 1993

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