• 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