Picture grammars in classification and semantic interpretation of 3D coronary vessels visualisations

The work presents the new opportunity for making semantic descriptions and analysis of medical structures, especially coronary vessels CT spatial reconstructions, with the use of AI graph-based linguistic formalisms. In the paper there will be discussed the manners of applying methods of computational intelligence to the development of a syntactic semantic description of spatial visualisations of the heart’s coronary vessels. Such descriptions may be used for both smart ordering of images while archiving them and for their semantic searches in medical multimedia databases. Presented methodology of analysis can furthermore be used for attaining other goals related performance of computer-assisted semantic interpretation of selected elements and/or the entire 3D structure of the coronary vascular tree. These goals are achieved through the use of graph-based image formalisms based on IE graphs generating grammars that allow discovering and automatic semantic interpretation of irregularities visualised on the images obtained during diagnostic examinations of the heart muscle. The basis for the construction of 3D reconstructions of biological objects used in this work are visualisations obtained from helical CT scans, yet the method itself may be applied also for other methods of medical 3D images acquisition. The obtained semantic information makes it possible to make a description of the structure focused on the semantics of various morphological forms of the visualised vessels from the point of view of the operation of coronary circulation and the blood supply of the heart muscle. Thanks to these, the analysis conducted allows fast and — to a great degree — automated interpretation of the semantics of various morphological changes in the coronary vascular tree, and especially makes it possible to detect these stenoses in the lumen of the vessels that can cause critical decrease in blood supply to extensive or especially important fragments of the heart muscle.

[1]  Paul Suetens,et al.  Temporal subtraction of thorax CR images using a statistical deformation model , 2003, IEEE Transactions on Medical Imaging.

[2]  Mark A. van Buchem,et al.  GAMEs: Growing and adaptive meshes for fully automatic shape modeling and analysis , 2007, Medical Image Anal..

[3]  Marco Mazzucco,et al.  A system for determination of 3D vessel tree centerlines from biplane images , 2004, The International Journal of Cardiac Imaging.

[4]  M. Gabriel Khan,et al.  Heart Disease Diagnosis and Therapy , 2005 .

[5]  J Keegan,et al.  Coronary artery imaging in grown up congenital heart disease: complementary role of magnetic resonance and x-ray coronary angiography. , 2000, Circulation.

[6]  Mariusz Flasiński Review of Medical image understanding technology - artificial intelligence and soft-computing for image understanding by Ryszard Tadeusiewicz, Marek R. Ogiela, Springer Verlag 2004 , 2004 .

[7]  Marek R. Ogiela,et al.  Modern Computational Intelligence Methods for the Interpretation of Medical Images , 2008, Studies in Computational Intelligence.

[8]  Isaac N. Bankman,et al.  Handbook of Medical Imaging. Processing and Analysis , 2002 .

[9]  Udo Hoffmann,et al.  Extent and distribution of coronary artery disease: a comparative study of invasive versus noninvasive angiography with computed angiography. , 2007, American heart journal.

[10]  Rainer J. Zotz,et al.  Fragment Reconstruction of Coronary Arteries by Transesophageal Echocardiography. A Method for Visualizing Coronary Arteries With Ultrasound , 2002 .

[11]  Paul Suetens,et al.  Minimal Shape and Intensity Cost Path Segmentation , 2007, IEEE Transactions on Medical Imaging.

[12]  Marek R. Ogiela,et al.  Medical Image Understanding Technology - Artificial Intelligence and Soft-Computing for Image Understanding , 2004, Studies in Fuzziness and Soft Computing.

[13]  W.E. Higgins,et al.  System for analyzing high-resolution three-dimensional coronary angiograms , 1996, IEEE Trans. Medical Imaging.

[14]  Marek R. Ogiela,et al.  Nonlinear processing and semantic content analysis in medical imaging , 2003, IEEE International Symposium on Intelligent Signal Processing, 2003.

[15]  Udo Hoffmann,et al.  Arterial wall imaging: evaluation with 16-section multidetector CT in blood vessel phantoms and ex vivo coronary arteries. , 2006, Radiology.

[16]  Philipp S Wild,et al.  Fragment Reconstruction of Coronary Arteries by Transesophageal Echocardiography: A Method for Visualizing Coronary Arteries With Ultrasound , 2002, Circulation.

[17]  F. Netter Atlas of Human Anatomy , 1967 .

[18]  Anke Meyer-Bäse,et al.  Pattern recognition for medical imaging , 2003 .

[19]  Marek R. Ogiela,et al.  Graph image language techniques supporting radiological, hand image interpretations , 2006, Comput. Vis. Image Underst..

[20]  Joseph M. Reinhardt 10.3 – Cardiac Image Processing , 2005 .