DocumentCode :
3175160
Title :
Assessment of regions at risk from coronary X-ray imaging by Kohonen´s map
Author :
Coppini, G. ; Tamburini, E. ; Abbate, A.L. ; Valli, G.
Author_Institution :
Inst. of Clinical Physiol., CNR, Pisa, Italy
fYear :
1995
fDate :
10-13 Sept. 1995
Firstpage :
757
Lastpage :
760
Abstract :
In previous studies, we have reported on: a) the three-dimensional reconstruction of coronary trees from bi-plane angiography, and b) the recovery of heart surface from epicardial vessels. On the ground of such works, we have developed a computational model of the spatial distribution of myocardial vascularization. The proposed model is based a on self-organizing neural network of the Kohonen´s type. This allows the computation of an optimal topology-preserving map of the arterial tree onto the epicardium. The availability of such a map permits the computation of the areas at risk directly from X-ray angiography. Preliminary results from clinical data are illustrated.
Keywords :
angiocardiography; diagnostic radiography; image reconstruction; mathematical morphology; medical image processing; physiological models; self-organising feature maps; Kohonen map; arterial tree; bi-plane angiography; clinical data; computational model; coronary X-ray imaging; coronary trees; epicardial vessels; epicardium; heart surface recovery; myocardial vascularization; optimal topology-preserving map; regions at risk; self-organizing neural network; spatial distribution; three-dimensional reconstruction; Angiography; Animals; Arteries; Computational modeling; Distributed computing; Heart; Myocardium; Neural networks; Skeleton; X-ray imaging;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers in Cardiology 1995
Conference_Location :
Vienna, Austria
Print_ISBN :
0-7803-3053-6
Type :
conf
DOI :
10.1109/CIC.1995.482775
Filename :
482775
Link To Document :
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